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Utility of Dissociated Intrinsic Hand Muscle Atrophy in the Diagnosis of Amyotrophic Lateral Sclerosis

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Electromyography Parameters to Discriminate Hand Osteoarthritis and Infer Their Functional Impact.

Verónica Gracia-Ibáñez¹, Mahdi Mohseni², Angela E Kedgley²

¹Department of Mechanical Engineering and Construction, Universitat Jaume I, 12071 Castelló de la Plana, Spain.

Sensors (Basel, Switzerland)

|October 26, 2024

Summary

Surface-electromyography (sEMG) can differentiate hand osteoarthritis patients from healthy individuals. Using specific normalization and waveform parameters during the Sollerman test achieved a 90.2% success rate for diagnosis.

Keywords:

diagnosis discriminant analysis electromyography hand function hand osteoarthritis

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Area of Science:

Biomedical Engineering
Rehabilitation Medicine
Clinical Diagnostics

Background:

Surface-electromyography (sEMG) is valuable for assessing muscle activation in hand pathologies.
Normalization methods and functional indicator use of sEMG require further investigation.

Purpose of the Study:

To differentiate between healthy individuals and patients with hand osteoarthritis (HOA) using forearm muscle sEMG signals.
To evaluate the impact of different normalization techniques on diagnostic accuracy.

Main Methods:

sEMG data collected from 21 healthy women and 20 women with HOA during the Sollerman test.
Amplitude (median, range) and waveform (new-zero-crossing, enhanced-wavelength) parameters analyzed.
Normalization using maximum signals during Sollerman tasks (MAX), maximum voluntary contraction (MVC), and maximum effort grasping (GRASP).

Main Results:

MVC and GRASP normalization methods yielded higher sEMG values in HOA patients.
Amplitude-based parameters showed lower diagnostic success rates.
Combining MAX-normalized amplitude and waveform parameters, using only Sollerman tasks, achieved 90.2% diagnostic accuracy.

Conclusions:

Normalization methods significantly influence sEMG diagnostic accuracy for HOA.
Waveform parameters show promise as reliable indicators of hand pathology.
sEMG, particularly with optimized normalization and parameter selection, can serve as a valuable diagnostic tool for HOA, inferring functional impact.