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Updated: Nov 22, 2025

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

Published on: April 21, 2017

Accelerometry as an objective measure of upper-extremity activity.

Samuel Larrivée¹, Emma Avery², Jeff Leiter^2,3

¹Department of Surgery, Section of Orthopaedic Surgery, Rady Faculty of Health Sciences, University of Manitoba, AD4 - 820 Sherbrook St., Winnipeg, MB, R3A 1R9, Canada. larrives@myumanitoba.ca.

Medical & Biological Engineering & Computing

|January 7, 2021

Summary

Wearable accelerometers can objectively measure shoulder activity, overcoming limitations of subjective questionnaires. A wrist-based device offers excellent sensitivity for long-term monitoring, while upper arm and chest placement provides optimal accuracy.

Keywords:

Activity count Shoulder Unsupervised monitoring Wearable sensors

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Last Updated: Nov 22, 2025

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

Published on: April 21, 2017

Capturing Representative Hand Use at Home Using Egocentric Video in Individuals with Upper Limb Impairment

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Published on: December 23, 2020

Home-Based Monitor for Gait and Activity Analysis

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

Area of Science:

Biomedical Engineering
Orthopedics
Sports Medicine

Background:

Current shoulder treatment effectiveness relies heavily on subjective patient-reported outcomes.
Validated objective tools for measuring shoulder-specific functional activity are lacking.

Purpose of the Study:

To validate wearable accelerometers as an objective measure of shoulder activity.
To identify optimal accelerometer placement and configuration for activity classification.

Main Methods:

Ten healthy volunteers participated in the study.
Accelerometers were placed on wrists, upper arm, and chest during standardized activities.
Tridimensional acceleration data were processed into activity counts using 10-second epochs.

Main Results:

Wrist-based accelerometers achieved an Area Under the ROC Curve (AUC) of 0.779 with 94.1% sensitivity and 67.5% specificity.
Combined upper arm and chest placement yielded an optimal AUC of 0.985 (94.8% sensitivity, 94.8% specificity).

Conclusions:

Dual-accelerometer placement (upper arm and chest) is the most accurate configuration for classifying shoulder activity.
A single wrist-based accelerometer serves as a viable objective proxy for shoulder activity in unsupervised, long-term monitoring.