Massimo Sartori

Massimo Sartori
University of Twente | UT · Department of Biomechanical Engineering

PhD
Chair of Neuromechanical Engineering, PI, Neuromechanical Modelling and Engineering Lab

About

121
Publications
48,489
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
2,530
Citations
Introduction
Dr Sartori's research interests include the development of methods for bridging between neural and functional understanding of human movement in vivo, and the translation of these to the development of advanced model-based control paradigms for neurorehabilitation technologies. More at: - https://twitter.com/MassimoSartori8 - https://loop.frontiersin.org/people/58825/ - https://scholar.google.de/citations?user=-d7_dAoAAAAJ&hl=en - https://www.linkedin.com/in/massimo-sartori-0612296/
Additional affiliations
April 2017 - present
University of Twente
Position
  • Professor
October 2016 - March 2017
Universitätsmedizin Göttingen
Position
  • Group Leader
June 2013 - September 2013
Stanford University
Position
  • Visiting Scholar
Description
  • Awarded an NIH visiting scholarship for developing computational musculoskeletal models of human movement.
Education
January 2008 - April 2011
University of Padova
Field of study
September 2004 - April 2007
University of Padova
Field of study
September 2001 - June 2004
University of Padova
Field of study

Publications

Publications (121)
Article
Full-text available
This position paper proposes a modeling pipeline to develop clinically relevant neuromusculoskeletal models to understand and treat complex neurological disorders. Although applicable to a variety of neurological conditions, we provide direct pipeline applicative examples in the context of cerebral palsy (CP). This paper highlights technologies in:...
Article
Full-text available
Objectives: The development of neurorehabilitation technologies requires the profound understanding of the mechanisms underlying an individual's motor ability and impairment. A major factor limiting this understanding is the difficulty of bridging between events taking place at the neurophysiologic level (i.e., motor neuron firings) with those eme...
Article
The intuitive control of upper-limb prostheses requires a man/machine interface that directly exploits biological signals. Here, we define and experimentally test an offline man/machine interface that takes advantage of the discharge timings of spinal motor neurons. The motor-neuron behaviour is identified by deconvolution of the electrical activit...
Conference Paper
The efficacy of trans-spinal direct current stimulation (tsDCS) as neurorehabilitation technology remains sub-optimal, partly due to the variability introduced by subject-specific neurophysiological features and stimulation conditions (e.g. electrode placement, stimulating amplitude, polarity, etc.) Hence, current therapies apply tsDCS in an open-l...
Article
The design of personalized movement training and rehabilitation pipelines relies on the ability of assessing the activation of individual muscles concurrently with the resulting joint torques exerted during functional movements. Despite advances in motion capturing, force sensing and bio-electrical recording technologies, the estimation of muscle a...
Article
Low back joint compression forces have been linked to the development of chronic back pain. Back-support exoskeletons controllers based on low back compression force estimates could potentially reduce the incidence of chronic pain. However, progress has been hampered by the lack of robust and accurate methods for compression force estimation. Elect...
Article
While a decreasing spectral content of surface electromyography reflects low back muscle fatigue development, reliability of these decreases may be insufficient. Decreasing frequency content is largely determined by decreasing average motor unit action potential conduction velocities (CV), which is considered a more direct measure of muscle fatigue...
Preprint
Full-text available
Embodied agents in continuous control domains have had limited exposure to tasks allowing to explore musculoskeletal properties that enable agile and nimble behaviors in biological beings. The sophistication behind neuro-musculoskeletal control can pose new challenges for the motor learning community. At the same time, agents solving complex neural...
Chapter
The paper describes the activities of the European project SOPHIA, Socio-Physical Interaction Skills for Cooperative Human-Robot Systems in Agile Production. The consortium involves European partners from academia, research organizations and industry. The main goal of the project is to develop a new generation of CoBots and Wearbots and advanced in...
Chapter
Full-text available
Lower limb prosthetic technology has greatly advanced in the last decade, but there are still many challenges that need to be tackled to allow amputees to walk efficiently and safely on many different terrain conditions. Neuro-mechanical modelling and online simulations combined with somatosensory feedback, has the potential to address this challen...
Chapter
The effectiveness of exoskeletons could be enhanced by incorporating low back muscle fatigue estimates in their control. The aim of the present study was to evaluate whether low back muscle fatigue can be estimated using the spectral content of trunk extensor muscle high-density EMG (HDEMG) by considering the motor unit action potential conduction...
Chapter
Neuromusculoskeletal modeling driven by electromyograms (EMG) has shown the ability to predict joint torque for a wide variety of movements. Taking advantage of this, we connected a real-time version of an EMG-driven model to a bilateral ankle exoskeleton to continuously assist during a wide repertory of locomotion tasks. The advantage is that the...
Chapter
Electromyography (EMG)-driven neuromusculo-skeletal models (NMSM) are currently used to estimate joint moments and muscle forces during dynamic movements considering subject-specific neural-excitation patterns provided by the EMG data. However, these models are rarely adopted in routine clinical applications. This is partly due to limitations in ob...
Chapter
Joint impedance is a common way of representing human joint dynamics. Since ankle joint impedance varies within the gait cycle, time-varying system identification techniques can be used to estimate it. Commonly, time-varying system identification techniques assume repeatably of joint impedance over cyclic motions, without taking into consideration...
Chapter
Quantifying human joint stiffness in vivo during movement remains challenging. Well established stiffness estimation methods include system identification and the notion of quasi-stiffness, with experimental and conceptual limitations, respectively. Joint stiffness computation via biomechanical models is an emerging solution to overcome such limita...
Chapter
Current clinical diagnostic tools for post-stroke motor deficits are based on rapid but subjective evaluation. Greater accuracy could be provided in well-equipped biomechanical laboratories. However, this involves lengthy set-up, data acquisition, and offline data analysis available only days, or weeks, after the initial assessment, no longer refle...
Article
Full-text available
Personalization of gait neuroprosthetics is paramount to ensure their efficacy for users, who experience severe limitations in mobility without an assistive device. Our goal is to develop assistive devices that collaborate with and are tailored to their users, while allowing them to use as much of their existing capabilities as possible. Currently,...
Conference Paper
The in vivo estimation of α-motoneuron (MN) properties in humans is crucial to characterize the effect that neurorehabilitation technologies may elicit over the composite neuro-musculoskeletal system. Here, we combine biophysical neuronal modelling, high-density electromyography and convolutive blind-source separation along with numerical optimizat...
Conference Paper
Current clinical decision-making is based on rapid and subjective functional tests such as 10 m walking. Moreover, greater accuracy can be achieved at the expense of rapidity and costs. In biomechanical laboratories, advanced technologies and musculoskeletal modeling can quantitatively describe the biomechanical reasons underlying gait disorders. O...
Conference Paper
Restoring natural motor function in neurologically injured individuals is challenging, largely due to the lack of personalization in current neurorehabilitation technologies. Signal-driven neuro-musculoskeletal models may offer a novel paradigm for devising novel closed-loop rehabilitation strategies according to an individual's physiology. However...
Chapter
Biological actuators are different from their mechatronic counterparts in terms of form and function. In this chapter, we discuss a data-driven neuromechanical model-based approach to estimate how muscles are neurally recruited as well as how they contribute to actuate multiple biological joints.
Preprint
To enable the broad adoption of wearable robotic exoskeletons in medical and industrial settings, it is crucial they can effectively support large repertoires of movements. We propose a new human-machine interface to drive bilateral ankle exoskeletons during a range of 'unseen' walking conditions that were not used for establishing the control inte...
Article
Full-text available
In vivo joint stiffness estimation during time-varying conditions remains an open challenge. Multiple communities, e.g. system identification and biomechanics, have tackled the problem from different perspectives and using different methods, each of which entailing advantages and limitations, often complementary. System identification formulations...
Article
Electromyography (EMG)-driven neuromusculoskeletal modeling (NMSM) enables simulating the mechanical function of multiple muscle-tendon units as controlled by nervous system in the generation of complex movements. In the context of clinical assessment this may enable understanding biomechanical factor contributing to gait disorders such as one indu...
Article
Wearable technologies such as bionic limbs, robotic exoskeletons and neuromodulation devices have long been designed with the goal of enhancing human movement. However, current technologies have shown only modest results in healthy individuals and limited clinical impact. A central element hampering progress is that wearable technologies do not int...
Article
Full-text available
Due to the epochal changes introduced by “Industry 4.0”, it is getting harder to apply the varying approaches for biomechanical risk assessment of manual handling tasks used to prevent work-related musculoskeletal disorders (WMDs) considered within the International Standards for ergonomics. In fact, the innovative human–robot collaboration (HRC) s...
Article
Full-text available
Trans-spinal direct current stimulation (tsDCS) provides a non-invasive, clinically viable approach to potentially restore physiological neuromuscular function after neurological impairment, e.g., spinal cord injury (SCI). Use of tsDCS has been hampered by the inability of delivering stimulation patterns based on the activity of neural targets resp...
Article
Full-text available
Duchenne muscular dystrophy (DMD) is a genetic disorder that results in progressive muscular degeneration. Although medical advances increased their life expectancy, DMD individuals are still highly dependent on caregivers. Hand/wrist function is central for providing independence, and robotic exoskeletons are good candidates for effectively compen...
Article
Full-text available
The manufacturing industry is among the top wealthgenerating sectors of the global economy and accounted for 15.3% and 10%, respectively, of the total European and American workforce in 2018 [1], [2]. Despite its crucial role, manufacturing is facing a critical challenge based on a reduction of skilled labor availability. This trend is impos- ing a...
Article
Full-text available
We propose a myoelectric control method based on neural data regression and musculoskeletal modeling. This paradigm uses the timings of motor neuron discharges decoded by high-density surface electromyogram (HD-EMG) decomposition to estimate muscle excitations. The muscle excitations are then mapped into the kinematics of the wrist joint using forw...
Article
Full-text available
Despite advances in mechatronic design, the widespread adoption of wearable robots for supporting human mobility has been hampered by 1) ergonomic limitations in rigid exoskeletal structures and 2) the lack of human–machine interfaces (HMIs) capable of sensing musculoskeletal states and translating them into robot-control commands. We have develope...
Article
Full-text available
With recent improvements in healthcare, individuals with Duchenne muscular dystrophy (DMD) have prolonged life expectancy, and it is therefore vital to preserve their independence. Hand function plays a central role in maintaining independence in daily living. This requires sufficient grip force and the ability to modulate it with no substantially...
Article
Full-text available
Background: Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inab...
Conference Paper
An important goal in the design of next-generation exoskeletons and limb prostheses is to replicate human limb dynamics. Joint impedance determines the dynamic relation between joint displacement and torque. Joint stiffness is the position-dependent component of joint impedance and is key in postural control and movement. However, the mechanisms to...
Conference Paper
Joint stiffness estimation under dynamic conditions still remains a challenge. Current stiffness estimation methods often rely on the external perturbation of the joint. In this study, a novel 'perturbation-free' stiffness estimation method via electromyography (EMG)-driven musculoskeletal modeling was validated for the first time against system id...
Article
Full-text available
Achieving human-like locomotion with humanoid platforms often requires the use of variable stiffness actuators (VSAs) in multi-degree-of-freedom robotic joints. VSAs possess 2 motors for the control of both stiffness and equilibrium position. Hence, they add mass and mechanical complexity to the design of humanoids. Mass distribution of the legs is...
Article
Full-text available
Upper extremity function is affected by a variety of neurological conditions. Robotic exoskeletons offer a potential solution for motor restoration. However, their systematic adoption is limited by challenges relative to human intention detection and device control. This position paper offers a focused perspective on this topic. That is, on how kno...
Article
Full-text available
The motivation behind this research topic was to cut across conventional boundaries that separate movement neuroscience, biomechanics, and robotics. The aim was to underscore that brain and body collaborate to produce behavior in biological organisms. While this is a simple idea, compartmentalization in education and science has often artificially...
Article
The intuitive control of bionic arms requires estimation of amputee’s phantom arm movements from residual muscle bio-electric signals. The functional use of myoelectric arms relies on the ability of controlling large sets of degrees of freedom (> 3 DOFs) spanning elbow, forearm and wrist joints. This would assure optimal hand orientation in any env...
Chapter
Recent effort in exoskeleton control resulted in reduction of human metabolic consumption during ground-level walking. In this context, solutions that would enable biomechanical and metabolic benefits across large repertoires of motor tasks would be central in supporting the human in both medical and industrial scenarios. With this idea in mind we...
Chapter
Mind controlled bionic limbs promise to replace mechanical function of lost biological extremities and restore amputees’ motor capacity. State of the art approaches use machine learning for establishing a mapping function between electromyography (EMG) and joint kinematics. However, current approaches require frequent recalibration with lack of rob...
Chapter
Advances in neurophysiology are enabling understanding the neural processing underlying human movement, i.e. the recruitment of spinal motor neurons and the transmission of the resulting neural drive to the innervated muscle fibers. Similarly, advances in musculoskeletal modeling are enabling understanding movement mechanics at the level of muscle...
Research
Full-text available
For the first time, a person with Duchenne muscular dystrophy is controlling an active hand orthosis. In this case study, we decoded the hand motor intention of the participant, using direct sEMG, for the control of an underactuated hand orthosis we developed (SymbiHand). Link: https://www.youtube.com/watch?v=jpHjlFM0t3Y&feature=youtu.be
Article
Full-text available
Objectives: Robotic prosthetic limbs promise to replace mechanical function of lost biological extremities and restore amputees' capacity of moving and interacting with the environment. Despite recent advances in biocompatible electrodes, surgical procedures, and mechatronics, the impact of current solutions is hampered by the lack of intuitive an...
Article
Full-text available
Force is generated by muscle units according to the neural activation sent by motor neurons. The motor unit is therefore the interface between the neural coding of movement and the musculotendinous system. Here we propose a method to accurately measure the latency between an estimate of the neural drive to muscle and force. Further, we systematical...
Chapter
This chapter presents developments as part of the International Union of Physiological Sciences (IUPS) Physiome Project. Models are multiscale, multispatial and multiphysics, hence, suitable numerical tools and platforms have been developed to address these challenges for the musculoskeletal system. Firstly, we present modelling ontologies includin...
Article
Full-text available
One of the current challenges in human motor rehabilitation is the robust application of Brain-Machine Interfaces to assistive technologies such as powered lower limb exoskeletons. Reliable decoding of motor intentions and accurate timing of the robotic device actuation is fundamental to optimally enhance the patient's functional improvement. Sever...
Article
Full-text available
Human motor function emerges from the interaction between the neuromuscular and the musculoskeletal systems. Despite the knowledge of the mechanisms underlying neural and mechanical functions, there is no relevant understanding of the neuro-mechanical interplay in the neuro-musculo-skeletal system. This currently represents the major challenge to t...
Conference Paper
Full-text available
This work aims at estimating the musculoskeletal forces acting in the human lower extremity during locomotion on rough terrains. We employ computational models of the human neuro-musculoskeletal system that are informed by multi-modal movement data including foot-ground reaction forces, 3D marker trajectories and lower extremity electromyograms (EM...
Conference Paper
We evaluated the electromechanical delay (EMD) for the tibialis anterior (TA) muscle during the performance of time-varying ankle dorsiflexions. Subjects were asked to track a sinusoidal trajectory, for a range of amplitudes and frequencies. Motor unit (MU) action potential trains were identified from surface electromyography (EMG) decomposition an...
Article
Full-text available
Objective: Current clinical biomechanics involves lengthy data acquisition and time-consuming offline analyses with biomechanical models not operating in real-time for man-machine interfacing. We developed a method that enables online analysis of neuromusculoskeletal function in vivo in the intact human. Methods: We used electromyography (EMG)-d...
Chapter
Real-time electromyography (EMG) driven musculoskeletal (NMS) modeling estimates internal body biomechanical parameters and motor intentions. This is central for understanding the dynamics of user-exoskeleton interaction and for developing closed-loop user-exoskeleton interfaces that are intuitive and effective in promoting neuroplasticity. This ab...
Chapter
This abstract proposes a modeling methodology that enables reconstructing ankle joint mechanical function from muscle motor unit spike trains decomposed from high-density electromyography signals. The abstract outlines methods and results and discusses the implication that this approach can have for enhancing our understanding of the neuro-mechanic...
Chapter
Full-text available
In this paper we analyze the role of corticomuscular transmission for the time-varying force control. Corticospinal coherence is assessed during frequency-modulated isometric ankle dorsiflexions. Our preliminary results show a significant coupling between EEG signals and motor unit spike trains at the target frequency, suggesting that low-frequency...