Assessing upper limb functional use in daily life using accelerometry: A systematic review

Background

Upper limb dysfunctions are common and disabling in daily life. Accelerometer data are commonly used to describe upper limb use. However, different data analyzing methods are used to describe or classify upper limb use.

Research question

The purpose of this systematic review was to present an overview of the assessment and data-analysis methods using accelerometery, and to specify their accuracy and validity assessing upper limb functional use.

Methods

A systematic literature search was performed consulting the following databases: Pubmed, Embase, Scopus, Web of Science, Sport Discus, Clinical Trials, and International Clinical Trials Registry Platform. The applied search terms were upper limb, activity tracking, and functional activity. Studies were included when they reported the accuracy and/or validity results of accelerometer-based methods to describe upper limb functional use.

Results and significance

13 studies were included describing counts threshold analyzing methods, gross movement scores and machine learning models. Seven studies retrieved a medium score, and six received a low-quality score on the quality assessment scale. The classification accuracy of the machine learning models ranged from 68 % to 97 % for intrasubject accuracy and from 59 % to 92 % for intersubject accuracy, compared to video annotated data. Besides good accuracy scores, the machine learning models also retrieved high validity results. High accuracy results were furthermore retrieved for the counts threshold method. Based on the evaluated studies, objectively assessing upper limb functional use can be done accurately and valid using accelerometry and can be an added value to assess upper limb dysfunctions in daily clinical practice.