Use of smart watches for continual measurement of hand-arm vibration

Status:

completed 10/2016

Aims:

A standard for dosimeters is currently under development. The existing measurement and auxiliary equipment is too expensive, and requires a high level of specialist expertise, or is impractical. Risk assessments based upon estimates are imprecise and in some cases incorrect. The aim of this project as a whole was to evaluate the scope for the use of smart watches in order to provide users of vibrating equipment with continual information on their instantaneous exposure, to signal violation of exposure limits, and to store the measured values. The project was to clarify whether, despite the strong damping of the wrist and the considerable divergence between individuals, the vibration exposure can be recorded and evaluated in adequate quality. Development of the method and field trialling were conducted in the IFA's project component.

Activities/Methods:

In order to develop the method, the IFA recorded data (triaxial acceleration data, in some cases with microphone data) for typical vibrating tools on a number of test subjects and including a range of confounding influences (e.g. gloves, tool holding arrangement). The data were analysed and software for a prototype developed by the Fraunhofer Institute for Computer Graphics Research IGD. A range of statistical analysis methods were employed for the study. The IFA conducted in-plant field trials based upon the results.

Results:

The smart watches do not permit direct measurement of the vibration exposure. Based upon the vibration pattern however, they are able to identify the tool being used, and are therefore able to estimate the daily vibration dose based upon known vibration values and measurement of the duration of exposure.

Signal detection and the associated accuracy of the calculated daily dose are dependent upon the vibration frequency and amplitude of the tool being used by the operator. Inaccuracies resulting from damping of the wrists of the specific operator were reduced by means of a "learning phase" for the different vibration characteristics of the tools. At constant ambient noise conditions, the microphone data were used to enhance signal recognition.

It was shown to be possible in principle to estimate the vibration exposure; further studies are however required regarding use of the method in plants, and in particular in order to determine the limitations of use. In view of the dramatic development of smart watches with improved sensor technology, their use for the purposes of vibration protection can be anticipated.

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