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Abstract

Measuring Hand-Arm Vibration (HAV) exposure is important to prevent permanent injuries, such as the White Finger / Raynaud Syndrome. Current measuring solutions require an individual attachment of those work tools that emit considerable vibrations. These sensing instruments are expensive and usually require a setup by experts. Additionally , these attached sensors are bulky and wired, which may further increase the risk of accidents in occupational safety. For an easy use, we propose using a Smartwatch to estimate the HAV doses gathered throughout the day. By utilizing the Smartwatch's Inertial Measuring Unit (IMU) that is sampling up to 800Hz, we are capable of reconstructing vibrations up to 400Hz. This range sufficiently covers the majority of harmful HAV loads that occurs with work tools. Our approach is an inexpensive solution that provides a rough estimation to indicate a vibration overload. Our solution does not require the specific tool type or datasheet.
Hand-Arm Vibration Estimation Using A Commercial Smartwatch
Denys J.C. Matthies1, Marian Haescher2, Gerald Bieber2, Suranga Nanayakkara1
1 Augmented Human Lab, Auckland Bioengineering Institute, The University of Auckland, NZ {firstname}@ahlab.org
2 Fraunhofer Institute for Computer Graphics Research IGD, Rostock, GER {firstname.surname}@igd-r.fraunhofer.de
Abstract
Measuring Hand-Arm Vibration (HAV) exposure is im-
portant to prevent permanent injuries, such as the White
Finger / Raynaud Syndrome. Current measuring solutions
require an individual attachment of those work tools that
emit considerable vibrations. These sensing instruments
are expensive and usually require a setup by experts. Ad-
ditionally, these attached sensors are bulky and wired,
which may further increase the risk of accidents in occu-
pational safety. For an easy use, we propose using a
Smartwatch to estimate the HAV doses gathered through-
out the day. By utilizing the Smartwatch’s Inertial Measur-
ing Unit (IMU) that is sampling up to 800Hz, we are capa-
ble of reconstructing vibrations up to 400Hz. This range
sufficiently covers the majority of harmful HAV loads that
occurs with work tools. Our approach is an inexpensive
solution that provides a rough estimation to indicate a vi-
bration overload. Our solution does not require the spe-
cific tool type or datasheet.
Keywords:
Hand-Arm Vibration Estimation; Smartwatch; Sensing;
Accelerometer; HAV Exposure Dose.
Introduction
There have been many research investigations looking
into understanding the risks of injury from hand-transmit-
ted vibration and whole-body vibration by means of epi-
demiological studies [1]. The most crucial impact is the
Raynaud Syndrome [3], which is a vascular spasm that
negatively affects vessel blood flow. This can be caused
when exposed to cold or stress, such as operating work
tools that emit considerable vibrations [4] to the hand and
arm. Vibrotactile perception in the fingertips can become
numb on a short-term temporal or long-term basis [6].
When the human body to the exposure to vibrations with-
out limits, symptoms such as coldness of the hands, the
legs, hypesthesia of the fingers, tremor/shivering of the
fingers, dexterity disturbance, weakness of the hands,
mobility disturbance of the elbow, shoulder/neck stiffness,
low back pain, fatigue, headache, dizziness, tinnitus, and
hearing loss can occur. These symptoms have been evi-
dent among quarry workers in developing countries such
as Vietnam [7], where occupational safety is not highly
practiced.
Different methods and technologies based on measuring
Hand-Arm Vibration [5], such as using high-sensitive ac-
celerometers [8], are used to prevent such symptoms.
These dosimeters are precise and provide sampling rates
up to 5kHz. Since these technologies are usually expen-
sive and instrumenting work tools with additional sensors
may create an increased risk in occupational safety, using
wearable technology such as a Smartwatch is a logical
step. IMUs, in particular Accelerometers and Gyroscopes,
that are implemented in Smartwatches so far only ena-
bled sampling rates of up to 100Hz without kernel modifi-
cations. Determining an accurate HAV is insufficient with
this sampling rate, since emitted vibrations can exist be-
yond this frequency. Research explored a work-around
when attempting to measure HAV exposure doses with
Smartwatches [2], such as using the accelerometer in
conjunction with the microphone to identify the tool the
worker used. Once the tool is known, it’s specific HAV ra-
tio is being looked up from a database. However, this re-
quires the system to have access to a complete database
with all HAV ratios from a great variety of work tools.
Method
In this paper, we propose an alternative approach, in
which we use the IMU of a commercial Smartwatch to cal-
culate a rough estimation of the HAV received at the
user’s wrist. This way, measuring the exact HAV expo-
sure doses is not possible because of the signal absorp-
tion, signal coupling, and transmission loss between the
vibration emitter (tool) and wrist (Smartwatch IMU).
In fact, the current Android Wear OS (2.9 – based on An-
droid 8.0.0) provides a new direct channel to assess the
acceleration sensor. Apparently, new devices will be able
to sample the IMU with a frequency up to 800Hz. Follow-
ing the Nyquist–Shannon sampling theorem, frequencies
of 400Hz can be reconstructed accordingly. Although, this
may still appear too low to sense the full spectrum of the
vibration exposure, it enables us to read most critical root-
mean-square (r.m.s.) acceleration magnitude - repre-
sented as a frequency weighting curve Wh (see Figure 1).
Figure 1. Hand-arm vibration frequency weighting curve
Wh following ISO 5349-1:2001 [9]. The highlighted areas
shows the coverable frequencies.
Therefore, our hypothesis is that a commercial Smart-
watch is sensitive enough to provide an acceptable ap-
proximation of the actual HAV exposure doses.
14th Internatio nal Conference on Ha nd-Arm-Vibration,
21-24 May 2 019, Bonn, Germany.
© 2019 Copyright is held by the owner/author(s).
Preliminary Field Study
We developed a smartwatch app running on an autarkic
Android Smartwatch. We used the model Simvalley
AW420-RX running Android 4.2. The watch has a Cortex
A7, 1 GB RAM and incorporates a Bosch BMC050 IMU,
which quantizes +/- 2 g (19,62m/s2) with 12bit. The
weight of the watch is approximately 90 grams.
Figure 2. We ran a preliminary field study in metalworking
/ manufacturing. The participants were equipped with a
smartwatch running our app, as well as with a microphone
and a GoPRO to measure the ground truth data.
We selected a window size of 128 samples of accelera-
tion tuples while using 50Hz. We assume that any harmful
HAV occur between 025Hz, which can be measured by
the Smartwatch. We calculated the significant accelera-
tion of the Smartwatch within the 3D-area by this formula:
!"# $
%
&' ( '
)
*+, &- ( -
.
*+, &/ ( /
)
*+
Our assumption concludes that tools with a slow motor
and slow motions would also lead to a low acceleration.
Figure 3. Distribution of measured 3D-acceleration (jerk)
measured at the wrist.
It becomes clear by Figure 3 that not only emitted tool vi-
bration is sensed, but also any other motion the worker
performs in the workshop. Therefore, we suggest classi-
fying typical motions that occur with <no Tool> and to sub-
tract this from the daily exposure doses.
In our preliminary field study, we used a low sampling rate
that is only capable of reading limited vibrations. For fu-
ture research, we suggest utilizing Smartwatches with
high sampling rates to capture a wider spectrum.
Moreover, we found that the measured 3D-acceleration
force does not directly correlate to the HAV. We believe
this is mainly due to the non-linear absorption of the vi-
bration frequencies at the fingers, the hand, and the wrist.
Also, we noticed that the wristband’s tightness to have a
significant influence on sensing the 3D-acceleration force.
Taking these factors into account, we believe reproducing
the correct HAV exposure doses could be possible.
Discussion
As demonstrated in Figure 1, the most harmful HAV oc-
curs in the lower frequency spectrum between 2.5–50Hz.
Capturing these should be prioritised. While professional
sensing tools are usually expensive and impractical, we
propose using a Smartwatch to estimate these. However,
an exact measurement is not possible due to various pa-
rameters such as the contact pressure between hand and
tool, signal absorption by the joints, tightness of the wrist-
band, etc. Aside from these factors, smartwatches are be-
coming increasingly powerful. They can provide a greater
sampling rate and are capable of sensing an increased
range of the frequency load. Nevertheless, a professional
measurement equipment is still superior. The proposed
work-around in AGIS [2] may still be the state-of-the-art
when measuring a more accurate HAV with unmodified
Smartwatches. In fact, the advance of the increased sam-
pling rate with Smartwatches can also benefit a greater
tool detection. Sampling the IMU with 800Hz may provide
enough signal characteristics to identify tools based on
the accelerometer only. Once the tool is identified, looking
up the HAV intensity ratio from the datasheet for each tool
would still be next step to calculate the daily dose. We see
Smartwatches as the gatekeeper for calculating the expo-
sure duration of harmful vibrations. In the future, we envi-
sion smart wearables to enter different industry branches,
provided that the legislator paves the way. Furthermore,
we see this technology as being capable of registering the
exposures in a cadaster, namely to distinguish between
regional and branch specific workloads.
Conclusion
The advancements in IMU sensing enables an estimation
of HAV exposure with commercial Smartwatches. Still, an
accurate measurement is yet problematic. In particular,
we are required to account for the non-linear absorption
of vibration frequencies into the hand and the tightness of
the wristband. Calculating the exact HAV dose using a
Smartwatch is feasible when running a tool detection, but
which requires a large database and thus is impractical.
References
[1] Griffin, M., Lewis, C., Bovenzi, M., Lemerle, P., & Lundström,
R. (2004). Risks of Occupational Exposures to Hand-transmit-
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tional Conference on Hand-Arm Vibration, Las Vegas, Nevada.
[2] Matthies, D. J. C., Bieber, G., & Kaulbars, U. (2016). AGIS:
automated tool detection & hand-arm vibration estimation
using an unmodified smartwatch. In Proceedings of iWOAR
2016 (p. 8). ACM.
[3] Blunt, R. J., & Porter, J. M. (1981). Raynaud syndrome.
In Seminars in arthritis and rheumatism (Vol. 10, No. 4, pp.
282-308). WB Saunders.
[4] Bovenzi, M. (1998). Exposure-response relationship in the
hand-arm vibration syndrome: an overview of current epidemi-
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Corresponding Address
d.matthies@auckland.ac.nz
ResearchGate has not been able to resolve any citations for this publication.
Conference Paper
Full-text available
Over the past three decades, it has been known that long-lasting and intense hand-arm vibrations (HAV) can cause serious diseases, such as the Raynaud-/ White Finger-Syndrome. In order to protect workers nowadays, the long-term use of tools such as a drill, grinder, rotary hammer etc. underlie strict legal regulations. However, users rarely comply with these regulations because it is quite hard to manually estimate vibration intensity throughout the day. Therefore, we propose a wearable system that automatically counts the daily HAV exposure doses due to the fact that we are able to determine the currently used tool. With the implementation of AGIS, we demonstrate the technical feasibility of using the integrated microphone and accelerometer from a commercial smartwatch. In contrast to prior works, our approach does not require a technical modification of the smartwatch nor an instrumentation of the environment or the tool. A pilot study shows our proof-of-concept to be applicable in real workshop environments.
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This paper provides an overview of the exposure-response relationship for the vascular component of the hand-arm vibration syndrome, called vibration-induced white finger (VWF). Over the past two decades, several epidemiological studies have shown a poor agreement between the risk for VWF observed in various occupational groups and that predicted by models included in annexes to International Standard ISO 5349 (ISO 5349:1986, ISO 5349-1:2001). Either overestimation or underestimation of the occurrence of VWF have been reported by investigators. It has been argued that the current ISO frequency-weighting curve for hand-transmitted vibration, which assumes that vibration-induced adverse health effects are inversely related to the frequency of vibration between 16 and 1250 Hz, may be unsuitable for the assessment of VWF. To investigate this issue, a prospective cohort study was carried out to explore the performance of four alternative frequency weightings for hand-transmitted vibration to predict the incidence of VWF in groups of forestry and stone workers. The findings of this study suggested that measures of vibration exposure which give relatively more weight to intermediate and high frequency vibration produced better predictions of the incidence of VWF than that obtained with the frequency weighting currently recommended in International Standard ISO 5349-1:2001.
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The complex of vascular, neurologic, and osteoarticular disorders occurring in the upper limbs of vibration-exposed workers is called hand-arm vibration syndrome. There is epidemiologic evidence for an increased occurrence of peripheral sensorineural disorders in occupational groups working with vibrating tools. An excess risk for wrist osteoarthrosis and for elbow arthrosis and osteophytosis has been reported in workers exposed to shocks and low-frequency vibration of high magnitude from percussive tools. However, there are too few epidemiology data to enable reliable conclusions to be drawn about exposure-response relationships for both sensorineural disturbances and bone and joint disorders caused by hand-transmitted vibration. Cross-sectional and longitudinal epidemiology studies have shown that occupational exposure to hand-transmitted vibration from a great variety of hand-held tools is significantly associated with an increased occurrence of digital vasospastic disorders called vibration-induced white finger (VWF). The proposal of an exposure-response relationship for VWF has been included in an annex to the international standard ISO 5349. The findings of several epidemiology studies have shown a poor agreement between the risk for VWF observed in various occupational groups and that predicted by the ISO 5349 model. Both overestimation and underestimation of the occurrence of VWF have been reported by investigators. It has been argued that the current ISO frequency-weighting curve for hand-transmitted vibration may be inappropriate for the assessment of vibration-induced adverse vascular effects. Alternative exposure-response relationships for VWF have been suggested in recent epidemiology studies. The epidemiology data used to construct current exposure-response relationships for vibration-induced injuries are primarily derived from cross-sectional studies. Future epidemiology research should be based on prospective cohort studies because the design characteristics of such studies permit the study of cause-effect relationships and the formulation of etiologic hypotheses.
Conference Paper
VIBRISKS seeks to improve understanding of the risk of injury from hand-transmitted vibration and whole-body vibration by means of epidemiological studies supported by fundamental laboratory research. VIBRISKS is a consortium of six partners from six European countries (France, Germany, Italy, Sweden, The Netherlands, UK). The four-year research project, which commenced in 2003, involves three work packages devoted to hand-transmitted vibration and three work packages devoted to whole-body vibration. This paper summarizes the hand-transmitted vibration research. Work package 1 defines methods to be used in studies of disorders caused by hand-transmitted vibration in work package 2 and integrates the results of the epidemiological studies in work package 2 with the results of experimental and modeling studies in WP3 so as to define procedures that can be applied by occupational health workers for minimizing risk, screening exposed individuals and managing individuals with symptoms. Work package 2 involves longitudinal studies in workers exposed to hand-transmitted vibration. Work package 3 involves experimental studies of the acute effects of hand-transmitted vibration on vascular and neurological function and the development of a finite element model of the biodynamic responses of the finger to vibration and force.
Article
Measurement of hand-arm transmitted vibration is a relevant issue for human health and safety. Many measurement problems occur with conventional transducers. In this paper, new measurement techniques are proposed. The methodology is based on a laser scanning vibrometer. Those techniques can be applied in laboratory tests and also to perform field tests on hand-guided vibrating tools, vehicles, and machines. Results of tests performed on different subjects with their hand on three laboratory test devices, designed according to ISO standards, are presented. Comparison of simultaneous measurements performed by the vibrometer and by conventional techniques (accelerometer) has been carried out. Further work has been done in order to test film sensors for measurement of the contact force between the hand and the vibrating surface. First results are here illustrated of film sensor characterisation and mechanical impedance measurements at some points of hands of different subjects, obtained by the laser Doppler vibrometer and by the film sensor.
Article
Few studies have focused on the health effects of vibrating tools on workers in the tropical area. Work conditions and health effects related to rock drill operation were studied in 102 quarry workers, including 73 rock drill operators in Vietnam. We aimed to clarify (1) risk of vibration exposure, (2) occurrence of vibration-induced white finger (VWF), and (3) characteristics of hand-arm vibration syndrome (HAVS). Total weighted r.m.s. acceleration of the Chinese -or Russian-made rock drills, was 45-55 m/s(2). According to work observation studies, daily exposure time to vibration was 160-210 min. ISO5349 predicted that this exposure level would be associated with a high risk of HAVS in workers. We found no clear evidence of VWF. There may be several reasons why no worker exhibited VWF: (1) warmer work conditions, (2) younger and less experienced workers, (3) seasonal changes in work operations, and (4) healthy worker effect. On the other hand, 5-10% of rock drill operators might be suffering from moderate HAVS which was sensori-neural type dominant. There may be some characteristic features of HAVS among quarry workers in the tropical area.
Vibrotactile perception thresholds at the fingertip measured with and without a surround
  • Gongqiang Yu
  • Anthony J Brammer
  • Martin G Cherniack
Yu, Gongqiang, Brammer, Anthony J., Cherniack, Martin G. (2015). Vibrotactile perception thresholds at the fingertip measured with and without a surround. In Proceedings of the 13th International Conference on Hand-Arm Vibration.
Measurement of hand-transmitted vibration exposures
  • S Maeda
  • R G Dong
Maeda, S., & Dong, R. G. (2004). Measurement of hand-transmitted vibration exposures. In Proceedings of the 10th International Conference on Hand-Arm Vibration (p. 89).