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Molecular & Cellular Biomechanics 2025, 22(2), 763.
https://doi.org/10.62617/mcb763
1
Article
Kinetic elements and brushstroke dynamics in painting through the lens of
biomechanics
Zhenpeng Zhao
College of Art and Design, Huanghe Science and Technology University, Zhengzhou 450006, China; zhaozhenpeng001@outlook.com
Abstract: This study explores the biomechanics of brushstroke dynamics in painting, focusing
on the physical demands of different brushstroke types and their underlying kinetic elements.
Through an experimental method combining motion capture, force sensors, and
electromyography, we analyzed the joint angles, Muscle Activation (MA) patterns, and force
application across four brushstroke types: broad strokes, fine detail, stippling, and circular
motions. Key findings revealed that broad strokes required the most extensive range of motion,
with shoulder and elbow joint angles averaging 45°–60° and 30°–40°, respectively, reflecting
the involvement of larger muscle groups in creating expansive movements. Fine detail strokes,
in contrast, relied predominantly on wrist flexion and extension (15°–20°), necessitating
greater precision and stability from distal muscles. Force analysis showed that stippling
generated the highest mean force (10.2 N) due to repetitive dabbing motions, whereas fine
detail strokes exhibited minimal force variability, indicating controlled, delicate muscle
engagement. Electromyography data indicated peak MA in the extensor carpi radialis and
flexor carpi radialis during fine and circular strokes, highlighting the unique demands of
rotational and fine motor control in painting. These findings underscore the complex interplay
of movement, force, and MA required for different painting techniques, contributing valuable
insights for optimizing technique and preventing repetitive strain in artists. This research
provides a foundational biomechanical understanding of brushstroke execution, with
implications for art education, rehabilitation, and ergonomic interventions in the arts.
Keywords: biomechanics; brushstroke dynamics; motion capture; electromyography; force
analysis; muscle activation; joint kinematics; painting technique
1. Introduction
The art of painting has long been celebrated for its expressive power, intricate
techniques, and the physical skills it requires [1,2]. While often considered a primarily
visual medium, painting is also a biomechanically demanding activity, necessitating
precise control, endurance, and complex coordination of muscles and joints [3,4]. The
ability to create diverse brushstrokes, from sweeping, broad lines to delicate details,
relies on sophisticated interactions between Muscle Activation (MA), joint flexibility,
and motor control [5,6]. Despite its significance, the biomechanical analysis of
painting remains an underexplored field [7,8]. Understanding the biomechanical
elements of brushstroke execution can provide valuable insights for artists and art
educators in rehabilitation science, ergonomics, and art preservation [9,10].
Brushstrokes serve as the fundamental building blocks of painting. Different
types of strokes, such as broad strokes, fine detail work, stippling, and circular
motions, each require unique combinations of movement and muscle control [11].
Broad strokes, for instance, engage larger muscle groups and broader joint
movements, particularly involving the shoulder and elbow, facilitating expansive,
CITATION
Zhao Z. Kinetic elements and
brushstroke dynamics in painting
through the lens of biomechanics.
Molecular & Cellular Biomechanics.
2025; 22(2): 763.
https://doi.org/10.62617/mcb763
ARTICLE INFO
Received: 11 November 2024
Accepted: 3 December 2024
Available online: 17 January 2025
COPYRIGHT
Copyright © 2025 by author(s).
Molecular & Cellular Biomechanics
is published by Sin-Chn Scientific
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under the Creative Commons
Attribution (CC BY) license.
https://creativecommons.org/licenses/
by/4.0/
Molecular & Cellular Biomechanics 2025, 22(2), 763.
2
fluid motions [12,13]. In contrast, fine detail strokes rely more heavily on wrist and
finger control, demanding high levels of precision and stability [14]. These diverse
biomechanical requirements underscore the complexity of painting as a physical
activity and highlight the intricate ways that artists must adapt their movements to
achieve specific visual effects.
The biomechanics of brushstroke dynamics are influenced by various factors,
including the type of brush and medium, the positioning of the artist, and the intended
artistic effect [15]. For example, artists may alter the brush’s speed, pressure, and angle
to produce different textures, color blends, and expressive elements. Faster
brushstrokes may impart a sense of movement and spontaneity, while slower strokes
can add depth and concentration to the artwork [16]. Similarly, the force applied by
the artist directly affects the thickness, texture, and intensity of the stroke, creating a
rich vocabulary of expression that varies by style, genre, and cultural tradition [17,18].
In Chinese ink painting, for example, controlled, fluid strokes are valued for their
precision and grace, while in Western oil painting, the emphasis might be on the tactile
quality and layering of paint [19].
Biomechanical research has increasingly been applied to fine motor activities,
such as handwriting and surgical procedures, yet few studies have addressed its role
in artistic practices like painting [20]. By examining MA, joint angles, and motion
types in brushstroke execution, biomechanics can offer a structured, quantitative
perspective on the physical demands of painting [21]. For artists, this knowledge could
provide practical guidance on technique refinement, training approaches, and injury
prevention [22]. For researchers and practitioners in fields such as physical therapy
and occupational health, understanding the biomechanics of painting could inform
rehabilitation protocols for artists experiencing strain or injury due to repetitive motion
or poor ergonomic setup [23].
This study investigates the Kinetic Elements (KE) and brushstroke dynamics in
painting from a biomechanical perspective. Specifically, it examines how hand, wrist,
and forearm movements, MA patterns, and force application contribute to different
brushstroke techniques. Through an experimental approach using motion capture
technology, force sensors, and electromyography, this research aims to analyze the
distinct biomechanical requirements of various painting styles. The study seeks to
provide a foundation for understanding how physical movements translate into artistic
expression by quantifying movement kinematics, force distribution, and muscle
engagement across brushstroke types. This work contributes to a deeper understanding
of the physical processes behind a painting and highlights the potential for
interdisciplinary applications of biomechanics in the study of fine arts [24–28].
In the current biomechanical approach to painting, there is no synchronization of
kinetic and kinematic data with painting performance parameters. Little research
compares dynamic force patterns, movement economy, and the biomechanical
consequences of long painting sessions on accuracy and fatigue. Moreover, the impact
of tools on biomechanics is an area of the least research, which hampers the
development of new ergonomic tools for artists. Such gaps can be filled through para-
disciplinary research, which enhances understanding of the relationships between
biomechanics and artistic creativity regarding enhanced training and adaptive tool
requirements for various artistic demands [29,30].
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Biomechanics in painting studies motor coordination, muscle activation, and
joint kinematics when painting with a brush; kinetic factors include force, speed, and
the angle of the motion, and affect accuracy and smoothness. The painters practicing
the craft for years have accomplished those dynamics with the best neuromuscular
control, conserving energy and stabilizing the work. They are more variable, which
results in muscle fatigue and joint stress. The painter’s grip wrist effects and shoulder
movements differ from one brush size to the canvas direction. Biomechanical work
stresses the need to adopt ergonomic measures in an organizational setting, such as the
setup of workstations and painting posture, which can minimize the occurrence of RSI
and boost durability [31–36].
The rest of the paper is organized as follows: Section 2 discusses the theoretical
background of biomechanical principles in painting, including hand-wrist-forearm
movements, MA patterns, and motion types. Section 3 examines KE in brushstroke
techniques, analyzing various brushstroke styles, speed-force-trajectory relationships,
and their effects on artistic outcomes. Section 4 presents the methodology, detailing
participant characteristics and measurement apparatus. Section 5 describes the
experimental design and procedures, including task specifications, materials
standardization, and data collection protocols. Section 6 presents the results through
comprehensive analyses of joint angles, force application, EMG patterns, speed-
trajectory characteristics, fatigue indicators, and movement efficiency measures.
Finally, Section 7 concludes with a discussion of the findings’ implications for artistic
practice and future research directions.
2. Theoretical background
The biomechanics of motion in painting encompass complex interactions
between MA, joint dynamics, and motor control. This section explores the
fundamental biomechanical principles underlying hand, wrist, and forearm
movements during painting, emphasizing how these elements contribute to creating
varied brushstrokes. By analyzing the relationship between muscle coordination, joint
angles, and the types of motion involved, we can better understand how artists achieve
different artistic effects.
2.1. Biomechanical analysis of hand, wrist, and forearm movements
In painting, the coordinated motion of the hand, wrist, and forearm enables artists
to execute precise brushstrokes that vary in speed, pressure, and angle. The hand and
wrist, as distal components, handle fine control, while the forearm provides stability
and broader movements. Movements are enabled by activating flexor and extensor
muscle groups, which control the force and direction of strokes.
The primary muscles involved include the flexor carpi radialis and ulnaris, which
facilitate wrist flexion, and the extensor carpi radialis longus and brevis, which support
wrist extension. Supinator and pronator muscles in the forearm enable rotational
movements crucial for adjusting the brush’s angle and creating specific textures. Joint
movement in the wrist, mainly through flexion-extension and radial-ulnar deviation,
directly influences brushstroke length and shape. For example, radial deviation helps
Molecular & Cellular Biomechanics 2025, 22(2), 763.
4
produce shorter strokes with a sharper angle, while ulnar deviation facilitates broader,
sweeping motions.
The fingers’ metacarpophalangeal (MCP) and interphalangeal (IP) joints allow
subtle adjustments that refine the stroke’s thickness and texture. This intricate
interplay between the hand, wrist, and forearm muscles allows precise brush control,
essential for rendering fine details or producing expressive, bold lines.
2.2. Influence of MA, joint angles, and kinetic chains on brushstroke
execution
In biomechanical terms, a kinetic chain describes the sequence of connected
joints and muscles working together to perform a movement. In painting, this chain
begins with the shoulder as a stabilizing base, extends through the elbow, and
culminates in the wrist and fingers, where finer control is applied. Efficient energy
transfer along this kinetic chain is essential for maintaining fluidity in brushstrokes,
especially during complex or prolonged painting sessions.
MA patterns vary according to the type of brushstroke. Light brushstrokes require
minimal activation of flexor muscles, reducing strain on the wrist and forearm. In
contrast, heavier strokes involve greater activation of flexors and extensors to maintain
control over increased force. Joint angles, particularly at the wrist, influence the
brush’s orientation and the stroke’s dynamics. For instance, a more acute wrist flexion
angle produces a narrow, concentrated stroke, while a neutral wrist position allows for
broader, more fluid movements.
Control over joint angles also reduces fatigue, as excessive wrist flexion or
extension can increase stress on the tendons. The efficient use of the kinetic chain
minimizes unnecessary muscle strain and optimizes the fluidity of motion, enabling
artists to sustain precision over extended periods. This biomechanical efficiency is
significant in producing consistent brushstrokes, as minor variations in MA and joint
angles can result in differences in line thickness, texture, and visual impact.
2.3. Overview of motion types (linear and rotational) involved in painting
In painting, linear and rotational motions contribute to the diversity of
brushstrokes.
Linear motion involves moving the brush in a straight line, often achieved by
translating the hand along the canvas plane. This motion is typically guided by
shoulder or elbow movement, especially for longer strokes. Linear strokes require
maintaining a steady MA pattern to produce uniform lines or gradients. For example,
horizontal or vertical strokes may involve stable shoulder and elbow flexion while
minimizing wrist deviation, enabling precise control over the line’s direction and
length.
Rotational motion, on the other hand, involves pivoting around a joint, commonly
the wrist or forearm, to produce curved or circular strokes. The rotation of the forearm,
in particular, allows for the adjustment of brush angle without requiring significant
shifts in hand position. This motion is critical in creating circular or elliptical strokes,
often seen in shading or stippling techniques. Wrist rotation, such as pronation (inward
Molecular & Cellular Biomechanics 2025, 22(2), 763.
5
rotation) and supination (outward rotation), allows for nuanced control over the angle
and pressure of the brush, resulting in varied textures and line weights.
By alternating between linear and rotational motions, artists can seamlessly
transition from broad, sweeping strokes to detailed, controlled lines, enhancing the
painting’s visual complexity. This combination of motion types, facilitated by the
coordination of multiple joints and muscle groups, forms the foundation of dynamic
brushwork and contributes to the unique aesthetic qualities of the artwork.
3. KE in brushstroke techniques
The techniques and styles of brushstrokes in painting are as varied as the
biomechanical demands they place on the artist. Understanding the KE involved in
different brushstroke styles is essential for appreciating how artists use physical
movement to produce expressive, textured, and blended effects. This section examines
various brushstroke types, the specific biomechanical requirements associated with
each, and how speed, force, and trajectory impact the visual outcome.
3.1. Breakdown of various brushstroke styles and their biomechanical
requirements
Different brushstroke styles demand distinct biomechanical approaches, as each
requires a unique combination of muscle control, joint movement, and force
application:
1) Broad strokes: Broad strokes involve large, sweeping movements that typically
engage the shoulder and elbow joints rather than relying on wrist and finger
precision. These strokes require stability and sustained control, as the brush must
frequently cover a large area uniformly. Engaging larger muscle groups in the
shoulder and upper arm allows consistent movement and reduces fatigue over
extensive strokes. Broad strokes create backgrounds, underpainting, or areas
requiring a wash of color.
2) Fine strokes: Fine strokes require high precision, focusing on wrist and finger
control rather than large arm movements. The muscles of the hand and forearm,
especially the flexors and extensors, play a central role in controlling small,
delicate movements. Fine strokes, such as lines or small shapes, are often used
for detailed work and require a stable wrist with minimal deviation to ensure
accuracy. The stability and coordination needed here are more significant, as any
slight variation can significantly affect the precision of the stroke.
3) Stippling: Stippling involves rapid, repeated dabbing of the brush against the
surface to create texture or shading effects through small dots or points.
Biomechanically, stippling requires repetitive, controlled wrist and finger
movements, often involving isometric MA to maintain a steady hand position.
This technique can induce localized muscle fatigue due to its repetitive nature,
especially in the wrist extensors, as they work to stabilize the hand.
Each style has specific biomechanical requirements tailored to its visual effect,
and understanding these requirements enables artists to optimize their techniques and
reduce fatigue or strain during prolonged sessions.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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3.2. Analysis of speed, force, and trajectory in executing different
brushstrokes
The KE of speed, force, and trajectory significantly impact the outcome of a
brushstroke:
• Speed: Speed of movement affects the thickness and opacity of a stroke. Faster
brushstrokes tend to be lighter and more translucent, as the bristles spend less
time on the canvas and apply less paint. Slower strokes allow for more paint
deposition and are often more saturated. For instance, rapid brushstrokes can
impart an impressionistic, spontaneous look, while slower strokes lend
themselves to controlled, intentional applications of color.
• Force: The force applied to the brush determines the pressure on the canvas and
the stroke’s depth and texture—light pressure results in soft, delicate strokes ideal
for creating ethereal effects or layering. Conversely, heavier pressure produces
bold, opaque strokes, which help define shapes or create a robust and vivid
impact. The forearm and hand muscles work together to modulate this pressure,
balancing firm strokes requiring muscle engagement and gentler strokes
emphasizing control.
• Trajectory: Trajectory, or the path the brush follows, is dictated by the angle and
curvature of movement. Straight trajectories create clean, linear strokes, while
curved or circular trajectories allow for rounded shapes or blended areas. The
wrist and shoulder primarily control the trajectory, depending on the
brushstroke’s length and the desired effect. For example, the shoulder may lead
in large arcs, while the wrist and fingers provide subtle adjustments in shorter,
curved strokes.
By manipulating speed, force, and trajectory, artists achieve a wide range of
textures and effects, adding depth and variation to their work. These elements are
central to the style and mood of a piece, as each variation influences how the paint
interacts with the canvas and how the brushstroke appears.
3.3. Discussion on how KE affects texture, color blending, and expression
in painting
Kinetic elements in brushstrokes are fundamental to an artwork’s textural
qualities, color blending, and overall expression:
• Texture: Texture is significantly influenced by the pressure and speed of a
brushstroke. For instance, dragging a dry brush lightly across the canvas creates
a textured, streaky effect, while a wet, heavy stroke leaves a smooth, filled-in
area. Artists often adjust their pressure and trajectory to emphasize or diminish
texture, depending on the intended aesthetic or emotional impact.
• Color blending: Blending colors smoothly requires controlled, overlapping
strokes at moderate speeds. Slow, deliberate strokes with light pressure help
gradually mix colors on the canvas without harsh boundaries. In contrast, rapid,
sporadic strokes lead to distinct, visible strokes that preserve the individuality of
each color. Biomechanically, smooth blending involves steady, controlled
movements with consistent pressure, reducing abrupt shifts that could disrupt the
blend.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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• Expression: KE in brushwork contributes to the expressive quality of a painting.
Dynamic, high-speed strokes create a sense of energy and movement, often
associated with impressionistic or abstract styles. Conversely, slow, methodical
strokes convey calmness and precision, often found in realistic or classical works.
Artists use variations in speed, pressure, and movement angles to imbue their
work with emotions or moods, making the kinetic quality of brushstrokes integral
to their expressive intent.
4. Methodology
4.1. Participants
The study recruited 21 participants (12 Females, 9 Males; Age Range: 20–45
Years, M = 32.4, SD = 7.2) from various art institutions in Henan Province, China. All
participants were right-handed professional artists or advanced art students with at
least five years of painting experience (range: 5–20 years, M = 8.6, SD = 4.3). The
sample included faculty members from the College of Art and Design at Huanghe
Science and Technology University (n = 7), professional artists from the Zhengzhou
Artists Association (n = 8), and advanced art students from the Henan University of
the Arts (n = 6).
Inclusion criteria required participants to:
• Have formal training in traditional Chinese or Western painting techniques;
• Practice painting regularly (minimum 10 h per week);
• Be free from any upper limb injuries or conditions that might affect painting
movement;
• Have no history of neurological disorders that could impact fine motor control.
The participants represented diverse painting specializations, including:
• Traditional Chinese painting (n = 8);
• Oil painting (n = 7);
• Watercolor (n = 6).
From Table 1, all participants provided written informed consent before
participating in the study. The research protocol was approved by the Ethics
Committee of Huanghe Science and Technology University (approval number:
HHSTU-202h42), and the study was conducted following the Declaration of Helsinki.
Table 1. Participant demographic characteristics (N = 21).
Characteristic
N
%
M (SD)
Range
Gender
Female
12
57.1
Male
9
42.9
Age (years)
32.4 (7.2)
20–45
20–30
8
38.1
31–40
9
42.9
41–45
4
19.0
Molecular & Cellular Biomechanics 2025, 22(2), 763.
8
Table 1. (Continued).
Characteristic
N
%
M (SD)
Range
Professional Status
Faculty Members
7
33.3
Professional Artists
8
38.1
Advanced Students
6
28.6
Painting Experience (years)
8.6 (4.3)
5–20
5–10
12
57.1
11–15
6
28.6
16–20
3
14.3
Specialization
Traditional Chinese
8
38.1
Oil Painting
7
33.3
Watercolor
6
28.6
Weekly Practice Hours
15.3 (5.8)
10–28
10–15
9
42.9
16–20
8
38.1
> 20
4
19.0
* Note: M = Mean; SD = Standard Deviation.
4.2. Apparatus and measurements
This study employed an integrated measurement system combining motion
capture technology, force sensors, and electromyography to analyze the biomechanical
components of brushstroke execution. The measurement setup was designed to capture
comprehensive data on movement kinematics, force application, and MA patterns
during painting tasks.
1) Motion capture system: The primary movement data was collected using a Vicon
Motion Systems (Oxford, UK) optical MCS comprising 10 infrared cameras
operating at 100 Hz. The cameras were arranged in a 360° configuration around
the painting workspace at heights ranging from 1.5 to 2.5 m. Twenty-four
reflective markers (12 mm diameter) were placed on specific anatomical
landmarks. The hand placement included 8 markers on the metacarpophalangeal
joints and carpometacarpal joints—the wrist configuration utilized four markers
on the radial and ulnar styloid processes. The forearm setup incorporated 6
markers on the lateral and medial epicondyles, while the upper arm placement
consisted of 6 markers on the acromion and deltoid tuberosity. The system
achieved a spatial accuracy of ±0.1 mm and a temporal resolution of 10 ms,
ensuring precise tracking of painting movements.
2) Force measurement system: Force data was captured using an ATI Nano17 six-
axis force/torque sensor (ATI Industrial Automation, Apex, NC) integrated into
a custom brush holder. The sensor specifications included a force measurement
range of ±50 N (x, y) and ±70 N (z), with a force resolution of 0.012 N. The torque
measurement range was set at ±500 N-mm, with a sampling rate of 1000 Hz and
Molecular & Cellular Biomechanics 2025, 22(2), 763.
9
a signal-to-noise ratio exceeding 50 dB. The sensor was calibrated before each
session using standardized weights to ensure measurement accuracy.
3) Electromyography system: MA patterns were recorded using a Delsys Trigno
Wireless EMG system (Delsys Inc., Natick, MA). Eight surface EMG sensors
were positioned to record activity from key muscle groups. The monitored
muscles included the Flexor Carpi Radialis (FCR), Flexor Carpi Ulnaris (FCU),
Extensor Carpi Radialis Longus (ECRL), Extensor Carpi Radialis Brevis
(ECRB), Pronator Teres (PT), supinator, brachioradialis, and upper trapezius.
EMG signals were sampled at 2000 Hz with a 20–450 Hz bandwidth and a
common mode rejection ratio exceeding 80 dB.
4) MA The integrated system captured various parameters across three main
categories. Kinematic measurements included joint angles, movement velocity,
and acceleration, all sampled at 100 Hz and measured in degrees and meters per
second. Kinetic measurements encompass normal force, shear force, and torque,
sampled at 1000 Hz and measured in Newton and Newton millimeters. Muscle
activity measurements included EMG amplitude, frequency content, and muscle
onset/offset timing, all sampled at 2000 Hz and measured in microvolts, Hertz,
and milliseconds.
5) Data processing and analysis: Raw data from all systems were synchronized
using a common trigger signal and processed through a comprehensive software
pipeline. The initial motion capture processing was conducted using Vicon Nexus
3.0, followed by EMG signal processing in EMG works 4.7.2. Custom MATLAB
R2023a scripts were developed for digital filtering using a 4th-order Butterworth
filter with a 6 Hz cut-off, movement segmentation, parameter calculation, and
statistical analysis. Data quality assurance was maintained through pre-session
calibration of all systems, real-time data collection monitoring, post-session
signal quality verification, and automated artifact detection and removal.
Tables 2 and 3 below describe the tools used, data collected, and measurement
parameters.
Table 2. Equipment specifications and measurement parameters.
System Component
Model/Manufacturer
Specifications
Measurement Parameters
Units
Motion Capture
Vicon Motion Systems (Oxford,
UK)
10 Cameras, 100 Hz Sampling
Rate, ±0.1 mm Accuracy
Angular Displacement
Degrees (°)
Linear Velocity
m/s
Acceleration
m/s2
Position Coordinates
mm
Force Sensor
ATI Nano17 (ATI Industrial
Automation, NC)
1000 Hz Sampling Rate
Normal Force
N
±50 N (x,y) Range
Shear Force
N
±70 N (z) Range
Torque
N-mm
0.012 N Resolution
Pressure
kPa
EMG System
Delsys Trigno (Delsys Inc., MA)
2000 Hz Sampling Rate
MA Amplitude
μV
20–450 Hz Bandwidth
Mean Frequency
Hz
> 80 dB CMRR
Median Frequency
Hz
Root Mean Square
μV
Molecular & Cellular Biomechanics 2025, 22(2), 763.
10
Table 2. (Continued).
System Component
Model/Manufacturer
Specifications
Measurement Parameters
Units
Data Processing
Vicon Nexus 3.0
Motion Data Processing
Movement Duration
s
EMG Works 4.7.2
EMG Analysis
Signal Intensity
Various
MATLAB R2023a
Custom Analysis
Statistical Parameters
Various
* Note: CMRR = Common Mode Rejection Ratio.
Table 3. Measurement parameters and their applications.
Category
Parameter
Sampling Rate
Purpose
Kinematic Analysis
Joint angles
100 Hz
Quantify the range of motion during
brushstrokes
Movement velocity
100 Hz
Assess brushstroke speed and fluidity
Movement
trajectory
100 Hz
Map spatial patterns of brush
movement
Force Analysis
Normal force
1000 Hz
Measure brush pressure on the surface
Shear force
1000 Hz
Analyze directional force components
Torque
1000 Hz
Evaluate rotational movements
Muscle Activity
EMG amplitude
2000 Hz
Measure MA intensity
Frequency content
2000 Hz
Assess muscle fatigue
Onset/offset timing
2000 Hz
Determine MA patterns
* Note: All measurements were synchronized using a common temporal reference frame.
5. Experimental design and procedure
5.1. Task environment and setup
The experimental environment maintained strict control over ambient conditions
to ensure standardized testing. A custom-designed workstation featuring adjustable
height (65–85 cm) accommodated various participant preferences while maintaining
optimal ergonomic positioning. Uniform lighting conditions (500 lux at canvas
surface) were established using calibrated LED panels to eliminate shadows and
ensure consistent visibility. The canvas surface was positioned at a 15° angle from the
horizontal, determined through pilot testing as optimal for brush manipulation while
minimizing wrist strain. Environmental conditions were monitored continuously,
maintaining room temperature at 22℃ ± 2℃ and relative humidity at 45% ± 5% to
ensure consistent paint viscosity and participant comfort.
5.2. Task specifications
The experimental protocol comprised four brushstroke tasks to evaluate specific
aspects of painting biomechanics and motor control. These tasks represented
fundamental techniques common in traditional Chinese and Western painting
practices, allowing for comprehensive analysis of varying biomechanical demands.
The broad stroke task evaluated participants’ ability to maintain consistent
pressure and fluid motion across extended movements, primarily engaging the
shoulder and elbow joints. This task was particularly relevant for understanding the
biomechanics of background painting and large-scale artistic elements. The fine detail
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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task challenged participants’ precise motor control, focusing on wrist and finger
coordination while creating intricate patterns. This task was essential for analyzing the
biomechanics of detailed artistic work and fine-line creation.
From Table 4, the stippling technique required participants to maintain rhythmic
movements while controlling force application, providing insights into the
biomechanics of repetitive painting motions. This task was crucial for understanding
muscle fatigue and motor control during repeated point-contact movements. The
circular stroke task examined participants’ ability to maintain smooth, controlled
rotational movements, combining linear and angular motion components. This task
was precious for analyzing the coordination between wrist rotation and arm movement
during curved brushwork.
Table 4. Brushstroke task parameters and requirements.
Task Type
Duration
Specifications
Technical Requirements
Rest Period
Broad Strokes
2 min
Width: 20–30 cm
Continuous Fluid motion
60 Sec
Coverage: Full Canvas
Width
Consistent PRESSURE
Direction: Horizontal
Shoulder/Elbow
Engagement
Fine Detail
2 min
Width: 1–3 mm
Precise Control
60 Sec
Grid: 5 × 5 cm squares
Wrist/Finger Coordination
Pattern: Linear
Minimal Tremor
Stippling
2 min
Density: 100 Points/Min
Regular Spacing
60 Sec
Area: 10 × 10 cm square
Consistent Force
Pattern: Uniform dots
Rhythmic Movement
Circular
2 min
Diameter: 5–15 cm
Smooth Rotation
60 Sec
Direction: Bi-Directional
Controlled Speed
Pattern: Concentric
Even spacing
5.3. Materials and equipment standardization
The selection and standardization of materials played a crucial role in ensuring
experimental consistency and data reliability. Each component was chosen based on
preliminary testing and professional artist consultation to represent typical tools while
meeting experimental control requirements.
From Table 5, the brush specification was determined through pilot testing to
balance control and flexibility optimally. The synthetic bristle composition ensured
consistent performance across multiple uses, while the standardized size and weight
maintained uniform mechanical properties throughout the experiment. Weekly
calibration checks verified that brush characteristics remained stable across all
participant sessions. Paint consistency was rigorously controlled through standardized
mixing protocols and regular viscosity testing. The 3:1 paint-to-water ratio was
maintained using precision measurements, and temperature monitoring ensured
consistent flow properties. Single-batch paint supplies eliminated potential variations
in pigment density or binding properties that could affect brush resistance during
strokes. The canvas selection balanced the need for consistent texture with practical
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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considerations for brush movement analysis. Medium-grain texture provided
sufficient friction for controlled brush movement while allowing for smooth stroke
execution. Pre-marked reference points on each canvas ensured consistent workspace
orientation and facilitated accurate motion capture data collection. All canvases were
sourced from a single manufacturing lot to eliminate potential variations in surface
properties.
Table 5. Standardized materials and equipment specifications.
Component
Specification
Control Parameters
Brush
Synthetic Bristle, Size 8
Single Manufacturer Model
Length: 20 cm
Pre-Tested for Consistency
Weight: 15 ± 1 g
Weekly Calibration Check
Paint
Medium viscosity acrylic
3:1 Paint-to-Water Ratio
Brand: [Specific Brand]
Single Batch Number
Viscosity: 250 ± 10 cP
Temperature Controlled
Canvas
Primed Cotton
40 × 40 cm Squares
Weight: 380 g/m2
Single Manufacturing Lot
Texture: Medium Grain
Pre-Marked Reference Points
5.4. Experimental protocol
The experimental protocol followed a systematic progression from preparation
through data collection. During the initial preparation phase, participants received
detailed instructions regarding brush handling techniques, sensor placement, and task
requirements. The familiarization period allowed participants 15 min of practice time
with the sensor-integrated brush holder, ensuring natural movement patterns were
maintained despite the presence of measurement equipment. Participants randomly
completed all four brushstroke tasks to minimize learning effects and fatigue bias.
Real-time monitoring of EMG signals allowed researchers to detect early signs of
muscle fatigue, with additional rest periods provided when necessary. The
standardized rest interval of 60 s between tasks proved sufficient for muscle recovery
while maintaining participant engagement throughout the session.
People with disorders of the upper limb musculoskeletal system, for example,
tendinitis or carpal tunnel syndrome, neurological disorders affecting motor control,
or systemic diseases affecting fatigue, are not allowed. Besides, participants with a
prior history of upper limb surgery or chronic pain in the arm that limits motion are
excluded from having clean biomechanical data.
5.5. Data collection and quality assurance
Implementing rigorous data collection protocols and quality control measures
was essential for maintaining experimental integrity. A multi-tiered approach to data
quality assurance was established, encompassing pre-session calibration, real-time
monitoring, and post-collection validation procedures.
Before each experimental session, a comprehensive system calibration protocol
was executed. The motion capture system underwent dynamic calibration using a
calibration wand, achieving residual errors below 0.2 mm across the capture volume.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Force sensors were zeroed and calibrated using standardized weights (100 g, 200 g,
500 g) to ensure linear response across the measurement range. EMG electrode
placement was verified through manual muscle testing and cross-talk assessment, with
electrode impedance maintained below 10 kΩ for optimal signal quality. Continuous
signal quality monitoring was performed through a dual-screen setup during data
collection. The first screen displayed real-time motion capture data, allowing
immediate detection of marker occlusion or tracking errors. The second screen showed
concurrent force and EMG signals, enabling researchers to identify anomalies in
sensor output or MA patterns. A dedicated research assistant monitored these
parameters throughout each session, documenting deviations from expected signal
characteristics.
From Table 6, the raw data underwent preliminary processing during collection
to verify signal integrity. Motion capture data was filtered using a fourth-order
Butterworth filter with a 6 Hz cut-off frequency, chosen based on power spectral
analysis of pilot data. Force sensor signals were processed using a 20 Hz low-pass
filter to remove high-frequency noise while preserving relevant force application
characteristics. EMG signals underwent bandpass filtering (20–450 Hz) and notch
filtering at 50 Hz to eliminate power line interference.
Table 6. Data collection parameters and quality controls.
System
Sampling Rate
Quality Measures
Validation Method
Motion Capture
100 Hz
Marker visibility > 95%
Real-time tracking verification
Spatial error < 0.2 mm
Pre-session calibration
Force Sensor
1000 Hz
Signal-to-noise > 50 dB
Zero-point calibration
Drift < 0.1% full scale
Known weight verification
EMG
2000 Hz
Baseline noise < 2 μV
Impedance check
Cross-talk < 5%
Maximum voluntary contraction
5.6. Data quality metrics
The MCS maintained marker visibility above 95% throughout the recording
period, with any gaps in marker trajectories less than 100 ms being eligible for
standard gap-filling algorithms. More significant gaps resulted in session repetition.
Force sensor drift was monitored through regular zero-point checks between tasks,
with the maximum allowable drift set at 0.1% of full scale. EMG signal quality was
assessed through baseline noise measurements and signal-to-noise ratio calculations,
with baseline noise required to remain below 2 μV and minimum signal-to-noise ratio
set at 20 dB.
Post-Collection Validation Following each session, data underwent automated
quality checks using custom MATLAB scripts.
These checks included:
1) Verification of temporal synchronization across all systems;
2) Assessment of signal continuity and sampling rate consistency;
3) Calculation of signal-to-noise ratios for all channels;
4) Detection of movement artifacts or signal anomalies;
5) Validation of kinematic consistency with anatomical constraints.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Sessions failing to meet quality criteria were flagged for review, and affected
tasks were repeated if necessary. This comprehensive data quality assurance approach
ensured the experimental results’ reliability and reproducibility, providing a solid
foundation for subsequent biomechanical analysis.
6. Result and discussion
6.1. Joint angle analysis
From Table 7, the Joint angle measurements revealed distinct patterns across
different brushstroke types, reflecting the varied biomechanical demands of each
technique. The analysis focused on the primary joints of brush manipulation: wrist,
elbow, and shoulder.
Table 7. Mean joint angle ranges during different brushstroke tasks (N = 21).
Joint Movement
Broad Strokes
Fine Detail
Stippling
Circular
F-value
p-value
Wrist Flexion/Extension (°)
Mean ± SD
35.4 ± 4.2
22.3 ± 2.8
18.7 ± 2.4
28.6 ± 3.7
24.63
< 0.001
Range
28.6–42.3
18.4–26.5
15.2–22.4
23.8–34.2
Wrist Radial/Ulnar Deviation (°)
Mean ± SD
24.8 ± 3.1
15.6 ± 2.2
12.4 ± 1.8
19.5 ± 2.6
18.92
< 0.001
Range
19.5–29.7
12.2–18.9
9.8–15.6
15.4–23.8
Elbow Flexion (°)
Mean ± SD
42.7 ± 5.3
15.8 ± 2.4
12.6 ± 1.9
28.4 ± 3.8
32.15
< 0.001
Range
34.2–51.4
12.1–19.2
9.4–15.8
22.6–34.5
Shoulder Flexion (°)
Mean ± SD
38.6 ± 4.8
12.4 ± 1.7
10.8 ± 1.5
22.7 ± 3.2
28.74
< 0.001
Range
31.2–45.8
9.8–15.6
8.2–13.5
17.4–28.3
* Note: All measurements represent the total range of motion during task execution. F-values and p-
values derived from one-way repeated measures ANOVA. SD = Standard Deviation.
Joint angle analysis (Figure 1) revealed significant differences across
brushstroke types for all measured joints (p < 0.001). Broad strokes consistently
required the most extensive range of motion across all joints, with wrist
flexion/extension showing the highest variability (SD = 4.2°). Fine detail work and
stippling demonstrated more constrained movement patterns, particularly in shoulder
and elbow joints, indicating more significant reliance on distal control. Circular
strokes showed intermediate ranges, reflecting the combined demands of rotational
and translational movements. The wrist joint exhibited task-specific patterns, with
flexion/extension ranges notably larger than radial/ulnar deviation across all tasks.
This difference was most pronounced during broad strokes (35.4° vs 24.8°) and least
pronounced during stippling (18.7° vs. 12.4°). These findings suggest that painters
preferentially utilize wrist flexion/extension over radial/ulnar deviation for brush
control, regardless of stroke type. Proximal joints (shoulder and elbow) showed greater
engagement during broad strokes than other techniques, with ranges approximately
three times larger than those observed during fine detail work. This pattern indicates
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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a transparent proximal-to-distal gradient in joint utilization across different
brushstroke types.
Figure 1. Mean joint angle ranges during different brushstroke tasks.
6.2. Force application analysis
The analysis of force application patterns across different brushstroke tasks
revealed distinct characteristics in magnitude, consistency, and directional
components. Force measurements captured through the sensor-integrated brush holder
provided insights into the mechanical demands of each painting technique.
Analysis of force application patterns (Table 8 and Figure 2) revealed significant
differences across brushstroke types (p < 0.001). Broad strokes demonstrated the
highest mean normal force (2.84 ± 0.42 N) and peak force values (3.95 ± 0.58 N),
consistent with the more significant muscle engagement required for these
movements. Fine detail work showed the lowest force magnitudes (mean: 1.26 ± 0.18
N) but exhibited higher variability in lateral force (CV = 19.0%). Stippling techniques
showed unique force features, with high temporal stability (89.2 ± 2.8%) and the
lowest lateral-to-normal force ratio (0.19 ± 0.03), indicating predominantly vertical
force application. Circular strokes demonstrated the highest lateral-to-normal force
ratio (0.41 ± 0.06), reflecting the continuous directional changes inherent in rotational
movements. Force consistency metrics revealed that stippling had the highest temporal
Molecular & Cellular Biomechanics 2025, 22(2), 763.
16
stability (89.2%) and spatial uniformity (87.6%), while fine detail work showed the
lowest values in both measures (82.6% and 79.4%, respectively). This pattern suggests
that maintaining consistent force is more challenging during precise, small-scale
movements than repetitive actions. The distribution of peak force events (Table 9)
shows distinct patterns across tasks, with broad strokes predominantly occurring in the
2.1–3.0 N range (45.8% of peaks), while fine detail work concentrated in lower force
ranges (91.9% below 2.0 N).
Table 8. Mean force parameters across brushstroke tasks (N = 21).
Force Parameter
Broad Strokes
Fine Detail
Stippling
Circular
F-value
p-value
Normal Force (N)
Mean ± SD
2.84 ± 0.42
1.26 ± 0.18
1.85 ± 0.24
1.92 ± 0.28
35.67
< 0.001
Peak
3.95 ± 0.58
1.74 ± 0.22
2.46 ± 0.31
2.68 ± 0.35
CV (%)
14.8 ± 2.1
14.3 ± 1.8
13.0 ± 1.6
14.6 ± 1.9
Lateral Force (N)
Mean ± SD
0.86 ± 0.12
0.42 ± 0.08
0.35 ± 0.06
0.78 ± 0.11
28.92
< 0.001
Peak
1.24 ± 0.18
0.58 ± 0.09
0.48 ± 0.08
1.12 ± 0.15
CV (%)
13.9 ± 1.8
19.0 ± 2.4
17.2 ± 2.1
14.1 ± 1.7
Force Ratio (Lateral/Normal)
Mean ± SD
0.30 ± 0.04
0.33 ± 0.05
0.19 ± 0.03
0.41 ± 0.06
22.45
< 0.001
Force Consistency
Temporal Stability (%)
88.4 ± 3.2
82.6 ± 4.1
89.2 ± 2.8
84.5 ± 3.6
19.83
< 0.001
Spatial Uniformity (%)
85.7 ± 3.8
79.4 ± 4.5
87.6 ± 3.1
81.2 ± 4.2
* Note: CV = Coefficient of Variation; Temporal Stability represents the percentage of time force
remaining within ± 15% of target value; Spatial Uniformity indicates the consistency of force
application across the stroke path.
Table 9. Distribution of peak force events across brushstroke tasks.
Category (N)
Broad Strokes
Fine Detail
Stippling
Circular
0.5–1.0
8.4
42.6
15.8
12.3
1.1–2.0
24.6
48.3
52.4
45.7
2.1–3.0
45.8
8.2
28.6
35.2
3.1–4.0
21.2
0.9
3.2
6.8
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Figure 2. Mean force parameters across brushstroke.
Both force patterns and artistic results are bound by the degree of forces applied
to control the dynamics of brushstrokes. Stoke length, curvature, and texture are
determined by changes in grip pressure, wrist motion, and angular velocity to allow
expressive control. If force is consistently applied, smoother tones are achieved, and
the stroke is transitioned smoothly with slight variation; when a great variety of force
is applied, a textured effect or a clear line is created. Lack of balance of forces may
negatively affect meaning in art and thus requires force adjustments.
6.3. EMG analysis and MA patterns
The electromyographic (EMG) data analysis revealed distinct MA patterns across
different brushstroke techniques, providing insights into the neuromuscular demands
of various painting tasks.
Pain during painting is caused by repetitive movements and postures in a fixed
position, mainly during the forearm, wrist, and shoulder muscles. Repetition of fine
motor control, for example, brush detail, strains the muscles targeted and experiences
fatigue, which results in tremors and, hence, decreased accuracy. Fatigue reduces
artistic consistency, particularly when accompanied by discomfort from poor
biomechanical postures that are made worse by prolonged sessions. Fatigue patterns
can be applied to ergonomics, allowing for grip alterations or rest to maintain optimal
motor performance and control.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Analysis of mean MA levels across brushstroke tasks revealed distinct patterns
in neuromuscular demands. As shown in Table 10 and Figure 3, the extensor carpi
radialis demonstrated the highest overall activation among all muscle groups, reaching
peak values of 58.5 ± 7.1 %MVC during broad strokes. Fine detail work consistently
showed the lowest activation levels across all muscles, with the flexor carpi radialis
operating at 24.3 ± 3.2 %MVC and flexor carpi ulnaris at 22.8 ± 2.9 %MVC. The
pronator teres exhibited task-specific activation patterns, showing the highest mean
activation during circular strokes (34.2 ± 4.2 %MVC) compared to other tasks, likely
due to the rotational demands of circular movements. Across all muscle groups, broad
strokes consistently required the highest activation levels, with peak values ranging
from 38.6 ± 4.8 %MVC for pronator teres to 58.5 ± 7.1 %MVC for extensor carpi
radialis, indicating the increased muscular demands of more significant painting
movements.
Table 10. Mean MA levels during brushstroke tasks (% of maximum voluntary
contraction).
Muscle Group
Broad Strokes
Fine Detail
Stippling
Circular
F-value
p-value
Flexor Carpi Radialis
Mean ± SD
38.6 ± 4.8
24.3 ± 3.2
28.7 ± 3.6
32.4 ± 4.1
42.35
< 0.001
Peak
52.4 ± 6.3
31.5 ± 4.2
38.2 ± 4.8
45.6 ± 5.4
Flexor Carpi Ulnaris
Mean ± SD
35.2 ± 4.4
22.8 ± 2.9
25.4 ± 3.2
30.6 ± 3.8
38.92
< 0.001
Peak
48.7 ± 5.8
29.4 ± 3.8
34.6 ± 4.3
42.3 ± 5.1
Extensor Carpi Radialis
Mean ± SD
42.8 ± 5.2
28.6 ± 3.5
32.4 ± 4.0
36.5 ± 4.5
45.63
< 0.001
Peak
58.5 ± 7.1
36.8 ± 4.6
43.2 ± 5.3
49.8 ± 6.0
Pronator Teres
Mean ± SD
28.4 ± 3.6
18.5 ± 2.4
21.6 ± 2.8
34.2 ± 4.2
36.78
< 0.001
Peak
38.6 ± 4.8
24.2 ± 3.1
28.5 ± 3.6
45.7 ± 5.5
* Note: All values are expressed as a percentage of maximum voluntary contraction (%MVC). Peak
values represent the 95th percentile of MA during each task.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Figure 3. Mean MA levels during brushstroke tasks.
The temporal characteristics and fatigue indicators presented in Table 11 and
Figure 4 revealed essential insights into the dynamic nature of muscle activation
during different brushstroke tasks. Stippling demonstrated the shortest burst durations
across all muscles, with the flexor carpi radialis showing bursts of 186 ± 24 ms and
extensor carpi radialis at 195 ± 26 ms. In contrast, broad strokes required sustained
muscle activation, with burst durations of 845 ± 95 ms for flexor carpi radialis and 892
± 102 ms for extensor carpi radialis. The co-activation index showed task-specific
patterns, with fine detail work requiring the highest co-activation (82.3% ± 9.6%)
despite its lower absolute activation levels. Fatigue indicators were most pronounced
during stippling, showing the most considerable median frequency shift (−5.6 ± 0.7
Hz) and RMS amplitude increase (18.2% ± 2.4%), suggesting that repetitive
movements may induce more significant muscular fatigue than sustained activations.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Figure 4. Temporal characteristics of MA.
Table 11. Temporal characteristics of MA.
Parameter
Broad Strokes
Fine Detail
Stippling
Circular
Mean Burst Duration (ms)
Flexor Carpi Radialis
845 ± 95
324 ± 42
186 ± 24
562 ± 68
Extensor Carpi Radialis
892 ± 102
348 ± 45
195 ± 26
584 ± 72
Co-activation Index (%)
Flexor-Extensor Pairs
64.5 ± 7.8
82.3 ± 9.6
75.8 ± 8.9
78.4 ± 9.2
Fatigue Indicators
Median Frequency Shift (Hz)
−4.2 ± 0.6
−2.8 ± 0.4
−5.6 ± 0.7
−3.8 ± 0.5
RMS Amplitude Increase (%)
15.4 ± 2.1
8.6 ± 1.2
18.2 ± 2.4
12.8 ± 1.8
6.4. Speed and trajectory analysis
Analysis of movement velocity data presented in Table 12 revealed significant
differences across brushstroke types (p < 0.001). Broad strokes demonstrated the
highest peak velocity (428.6 ± 52.4 mm/s) and mean velocity (285.4 ± 35.6 mm/s),
reflecting the sweeping nature of these movements. Fine detail work showed the
lowest velocities, with peak values of 156.3 ± 18.5 mm/s, indicating detailed
brushwork’s controlled, precise nature. Notably, the coefficient of variation remained
relatively consistent across all tasks (12.5%–12.8%), suggesting similar levels of
velocity control despite differing movement speeds.
The trajectory characteristics presented in Table 13 showed distinct patterns in
spatial and temporal parameters. Broad strokes covered the most significant path
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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length (285.6 ± 32.4 mm) with the longest movement time (1.24 ± 0.15 s), while
stippling exhibited the shortest path length (8.4 ± 1.2 mm) and movement time (0.06
± 0.01 s). Fine detail work demonstrated superior spatial accuracy with the lowest
spatial error (0.8 ± 0.1 mm) among all tasks. The smoothness index revealed that broad
strokes and stippling achieved the highest smoothness values (0.86 ± 0.04 and 0.84 ±
0.03 respectively), while fine detail work showed lower smoothness (0.72 ± 0.05),
likely due to the increased control demands of precise movements.
Table 12. Movement velocity and trajectory characteristics across brushstroke tasks
(N = 21).
Parameter
Broad Strokes
Fine Detail
Stippling
Circular
F-value
p-value
Peak Velocity (mm/s)
Mean ± SD
428.6 ± 52.4
156.3 ± 18.5
224.8 ± 28.6
342.5 ± 42.7
48.92
< 0.001
Range
324.5–532.8
125.4–187.2
178.5–271.2
268.4–416.8
Mean Velocity (mm/s)
Mean ± SD
285.4 ± 35.6
98.5 ± 12.4
142.6 ± 18.2
226.3 ± 28.5
52.36
< 0.001
CV (%)
12.5 ± 1.8
12.6 ± 1.6
12.8 ± 1.7
12.6 ± 1.5
Table 13. Spatial and temporal trajectory characteristics.
Trajectory Parameter
Broad Strokes
Fine Detail
Stippling
Circular
Path Length (mm)
Mean ± SD
285.6 ± 32.4
42.5 ± 5.8
8.4 ± 1.2
158.3 ± 18.6
Range
228.4–342.8
32.6–52.4
6.5–10.3
124.5–192.1
Movement Time (s)
Mean ± SD
1.24 ± 0.15
0.48 ± 0.06
0.06 ± 0.01
0.82 ± 0.10
Spatial Error (mm)
Mean ± SD
3.8 ± 0.5
0.8 ± 0.1
0.6 ± 0.1
2.4 ± 0.3
Smoothness Index
Mean ± SD
0.86 ± 0.04
0.72 ± 0.05
0.84 ± 0.03
0.78 ± 0.04
* Note: CV = Coefficient of Variation; Smoothness Index ranges from 0 (least smooth) to 1
(smoothest), calculated using normalized jerk score.
6.5. Fatigue analysis in extended painting sessions
Inexperienced painters display fast development of muscle fatigue because of
incorrect movement coordination and increased utilization of large muscles.
Professional painters portray enhanced stamina; they flex the stabilizing muscles that
are small well. Literature review shows that fatigue onset time may differ from 30%–
40%, consequently affecting painters’ skill and knowledge levels; more specifically,
the authors focused on the biomechanics of painters’ work.
Analysis of muscle fatigue indicators in Table 14 and Figure 5 revealed
significant changes in EMG parameters over the 2-min continuous task performance.
The flexor carpi radialis showed a 31.2% increase in RMS amplitude (p < 0.001) from
initial to final periods, accompanied by a 15.5% decrease in median frequency. More
pronounced changes were observed in the extensor carpi radialis, with a 36.8%
increase in RMS amplitude and a 16.9% decrease in median frequency. The power
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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ratio (Low/High Frequency) demonstrated the most dramatic changes, increasing by
90.8% and 103.4% for the flexor and extensor muscles, respectively, indicating
substantial manifestation of muscle fatigue.
Table 14. Muscle fatigue indicators during 2-min continuous task performance (N = 21).
Muscle Group
Time
Mean RMS Amplitude (%MVC)
Median Frequency (Hz)
Power Ratio (Low/High)
Flexor Carpi Radialis
Initial (0–30s)
32.4 ± 4.2
85.6 ± 8.4
0.65 ± 0.08
Middle (30–90s)
36.8 ± 4.8
78.4 ± 7.8
0.82 ± 0.10
Final (90–120s)
42.5 ± 5.4
72.3 ± 7.2
1.24 ± 0.15
Change (%)
+ 31.2*
− 15.5*
+ 90.8*
Extensor Carpi
Radialis
Initial (0–30s)
38.6 ± 4.8
92.4 ± 9.2
0.58 ± 0.07
Middle (30–90s)
44.2 ± 5.6
84.6 ± 8.5
0.76 ± 0.09
Final (90–120s)
52.8 ± 6.5
76.8 ± 7.6
1.18 ± 0.14
Change (%)
+ 36.8*
− 16.9*
+ 103.4*
* Note: * p < 0.001; %MVC = Percentage of Maximum Voluntary Contraction.
Figure 5. Muscle fatigue indicators during 2-min continuous task performance.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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The task-specific fatigue characteristics presented in Table 15 demonstrated
varying rates of fatigue development across different brushstroke types. Stippling
showed the highest fatigue development rate (22.8 ± 2.8 %/min) and required the
longest recovery time (52.6 ± 6.5 s) while exhibiting the shortest endurance time (82.4
± 10.4 s). In contrast, fine detail work demonstrated the lowest fatigue development
rate (12.6 ± 1.6 %/min) and shortest recovery time (32.4 ± 4.2 s), with the longest
endurance time (112.8 ± 14.2 s), suggesting that lower-intensity, precise movements
could be sustained for more extended periods despite the high attention demands.
Table 15. Task-specific fatigue development rates and recovery indicators.
Task Type
Fatigue Development Rate (%/min)
Recovery Time (s)
Endurance Time (s)
Broad Strokes
Mean ± SD
18.4 ± 2.3
45.6 ± 5.8
94.5 ± 11.8
Range
14.2–22.6
35.2–56.4
74.8–114.2
Fine Detail
Mean ± SD
12.6 ± 1.6
32.4 ± 4.2
112.8 ± 14.2
Range
9.8–15.4
24.8–40.2
88.5–136.4
Stippling
Mean ± SD
22.8 ± 2.8
52.6 ± 6.5
82.4 ± 10.4
Range
17.6–28.2
40.8–64.5
64.2–100.6
Circular
Mean ± SD
15.6 ± 1.9
38.5 ± 4.8
104.6 ± 13.2
Range
12.2–19.2
29.8–47.2
82.4–126.8
6.6. Kinematic and kinetic efficiency analysis
Analysis of movement efficiency metrics in Table 16 and Figure 6 revealed
significant differences across brushstroke types (p < 0.001). Broad strokes showed the
highest energy cost (4.82 ± 0.62 J/m) and path ratio (1.24 ± 0.15), indicating lower
movement economy compared to other techniques. Fine detail and stippling
demonstrated superior movement precision, with spatial errors of 0.84 ± 0.10 mm and
0.62 ± 0.08 mm, respectively, significantly lower than broad strokes (3.86 ± 0.48 mm)
and circular movements (2.45 ± 0.32 mm). The task-specific performance parameters
presented in Table 17 and Figure 7 showed distinct movement control and efficiency
patterns. Fine detail work exhibited the highest feedback gain (0.92 ± 0.11) and a high
correction rate (8.6 ± 1.1 Hz), reflecting the increased control demands of precise
movements. Stippling demonstrated the lowest efficiency ratio (8.3% ± 1.0%) but the
highest correction rate (12.4 ± 1.5 Hz), suggesting a trade-off between metabolic
efficiency and movement control. Broad strokes achieved the highest efficiency ratio
(19.9% ± 2.5%) despite their higher absolute energy cost, indicating better energy
utilization during large-scale movements.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Table 16. Movement efficiency metrics across brushstroke types (N = 21).
Efficiency Parameter
Broad Strokes
Fine Detail
Stippling
Circular
F-value
p-value
Movement Economy
Energy Cost (J/m)
4.82 ± 0.62
2.34 ± 0.28
1.86 ± 0.24
3.45 ± 0.42
38.64
< 0.001
Path Ratio
1.24 ± 0.15
1.08 ± 0.12
1.04 ± 0.11
1.18 ± 0.14
25.32
< 0.001
Movement Precision
Spatial Error (mm)
3.86 ± 0.48
0.84 ± 0.10
0.62 ± .08
2.45 ± 0.32
42.18
< 0.001
Temporal Variability (%)
12.4 ± 1.5
8.6 ± 1.1
6.8 ± 0.9
10.2 ± 1.3
34.75
< 0.001
Table 17. Task-specific performance and control parameters.
Control Parameter
Broad Strokes
Fine Detail
Stippling
Circular
Movement Time (s)
Mean ± SD
1.24 ± 0.15
0.48 ± 0.06
0.06 ± 0.01
0.82 ± 0.10
Optimal
1.08 ± 0.13
0.42 ± 0.05
0.05 ± 0.01
0.74 ± 0.09
Muscle Efficiency
Work Output (J)
0.86 ± 0.11
0.24 ± 0.03
0.12 ± 0.02
0.58 ± 0.07
Metabolic Cost (J)
4.32 ± 0.54
1.85 ± 0.23
1.45 ± 0.18
3.24 ± 0.41
Efficiency Ratio (%)
19.9 ± 2.5
13.0 ± 1.6
8.3 ± 1.0
17.9 ± 2.2
Control Strategy
Feedback Gain
0.68 ± 0.08
0.92 ± 0.11
0.84 ± 0.10
0.76 ± 0.09
Correction Rate (Hz)
4.2 ± 0.5
8.6 ± 1.1
12.4 ± 1.5
6.8 ± 0.8
* Note: Efficiency Ratio = (Work Output/Metabolic Cost) × 100; Feedback Gain ranges from 0 (Low
Control) to 1 (High Control)
Figure 6. Movement efficiency metrics across brushstroke types.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
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Figure 7. Task-specific performance and control parameters.
The biomechanical cost of moving through the paint space refers to the cost of
joint motion, or the least amount of effort needed to control the movement. Feedback
gain relates to the sensorimotor loop needed to make corrections based on what is
sensed when the hand is in movement to obtain the expected results regardless of the
movement. The high correction rates mean that the proprioceptive feedback is good,
but the high correction rate may be inefficient if it has to be corrected too often.
Sophisticated biomechanical models estimate positions and velocities, even reaction
time and precision rate, and measure performance and learning adaptations.
Underlining such stable hand trajectory and smooth acceleration patterns increases
kinematic efficiency, making it easy to master artistic works.
The biomechanical effects of painting materials differ significantly. Oil painting
is more of a constant muscular work because paint application entails thicker brushes
and dries slowly than acrylics; it entails constant grip force and stability, resulting in
wrist and shoulder straining. Because of its loose strokes and free-flowing movements,
Watercolor does not overly apply and maintain tension but requires fine muscle
control. Acrylics have some characteristics of both, requiring somewhat above-
average endurance and control. Fresco painting is predominantly an overhead job,
increasing shoulder and neck strain chances. These effects are magnified with tools,
including brush size and canvas orientation. For instance, horizontal canvases and
larger brushes contribute to more shoulder movement, while small brushes generally
require wrist movement.
Molecular & Cellular Biomechanics 2025, 22(2), 763.
26
7. Conclusion and future work
This study examined the biomechanical aspects of brushstroke dynamics in
painting, focusing on the physical requirements of different brushstroke techniques.
Through integrating motion capture, force sensors, and electromyography, we
captured detailed data on joint angles, muscle activation, and force application across
broad, fine-detail, stippling, and circular strokes. The findings demonstrate that each
brushstroke type imposes distinct biomechanical demands influenced by the range of
motion, muscle engagement, and force consistency. Broad strokes required substantial
shoulder and elbow involvement, allowing for expansive, fluid movements but also
placing increased demand on larger muscle groups. On the other hand, fine detail
strokes relied heavily on precise wrist and finger control, which required high levels
of stability and dexterity. The repetitive stippling strokes increased force levels and
muscle activation, suggesting an increased fatigue risk over extended sessions.
Circular strokes combine linear and rotational movements, activating the forearm and
wrist muscles and showcasing the complex motor coordination needed for smooth,
continuous motions. These insights highlight the importance of understanding the
biomechanics of painting to improve technique, enhance endurance, and minimize
strain. For art practitioners, incorporating knowledge of joint angles, force
distribution, and muscle activation patterns can inform more sustainable painting
practices. In addition, this research provides a foundation for developing ergonomic
guidelines and targeted training programs, which may benefit artists and art educators
aiming to optimize technique while preventing injury. In conclusion, this study
establishes a baseline for understanding the physical demands of painting from a
biomechanical perspective, bridging the gap between art and science.
Future research could extend this analysis to other forms of visual art, consider
different artistic tools and mediums, and explore long-term muscle and joint function
adaptations in professional artists. This work contributes to a holistic understanding of
the biomechanics behind creative practice by exploring the intricate relationship
between physical motion and artistic expression.
Ethical approval: Not applicable.
Conflict of interest: The author declares no conflict of interest.
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