Contact pressure in the wrist during computer mouse work

Mouse with your arm™: Facilitating forearm support using the chair armrest to prevent and mitigate musculoskeletal disorders

BACKGROUND

Musculoskeletal disorders (MSDs) can be prevented by avoiding trauma caused by poor posture, compression, force, and repetition. Neutral postures are recommended to avoid MSDs.

OBJECTIVE

This study introduces Mouse With Your Arm™ (MWYA) methodology which promotes sitting back in a chair, using the chair's armrest for forearm support at relaxed elbow height, matching surface and armrest height, and keeping the mouse on the surface edge. This position allows optimal task chair use, facilitates movement and neutral postures, avoids compression and contact stress, and is effective in mitigating MSDs.

METHOD

MWYA was applied and measured in the field for more 23 years providing over 3,500 individualized assessments to integrate a participant's unique characteristics, reported health concerns, tasks, tools, and environment to achieve and sustain whole-body neutral and comfortable working postures.

RESULTS

Previous research has consistently recommended use of forearm support by a desk, apparatus, or wrist rest, and resulted in non-neutral, static postures and measured health consequences. By using armrests for support, MWYA avoids the potential of MSDs as can be caused by these previously endorsed postures.

CONCLUSION

By applying the five MWYA principles, computer users comprehend neutral posture and put forth the effort essential to creating healthy human computer relationships.

A biomechanical study of spherical grip

Use of the hand is vital in working life due to the grabbing and pinching it performs. Spherical grip is the most commonly used, due to similarity to the gripping of a computer mouse. Knowledge of its execution and the involved elements is essential. Analysis of this exertion with surface electromyography devices (to register muscular activity) and accelerometer devices (to register movement values ) can provide multiple variables. Six subjects performed ball gripping and registered real-time electromyography (thenar region, hypothenar region, first dorsal interosseous, flexors of the wrist, flexor carpi ulnaris and extensors of the wrist muscles) and accelerometer (thumb, index, middle, ring, pinky and palm) values. The obtained data was resampled "R software" and processed "Matlab Script" based on an automatic numerical sequence recognition program. Electromyography values were normalized on the basis of maximum voluntary contraction, whilst modular values were calculated for the acceleration vector. After processing and analysing the obtained data and signal, it was possible to identify five stages of movement in accordance with the module vector from the palm. The statistical analysis of the variables was descriptive: average and standard deviations. The outcome variables focus on the variations of the modules of the vector (between the maximum and minimum values of each module and phase) and the maximum values of the standardized electromyography of each muscle. Analysis of movement through accelerometer and electromyography variables can give us an insight into the operation of spherical grip. The protocol and treatment data can be used as a system to complement existing assessments in the hand.