Accuracy and Validity of a Single Inertial Measurement Unit-Based System to Determine Upper Limb Kinematics for Medically Underserved Populations

Abstract

Stroke is one of the leading causes of death and disability worldwide, with a disproportionate burden represented by low- and middle-income countries (LMICs). To improve post-stroke outcomes in LMICs, researchers have sought to leverage emerging technologies that overcome traditional barriers associated with stroke management. One such technology, inertial measurement units (IMUs), exhibit great potential as a low-cost, portable means to evaluate and monitor patient progress during decentralized rehabilitation protocols. As such, the aim of the present study was to determine the ability of a low-cost single IMU sensor-based wearable system (named the T’ena sensor) to reliably and accurately assess movement quality and efficiency in physically and neurologically healthy adults. Upper limb movement kinematics measured by the T’ena sensor were compared to the gold standard reference system during three functional tasks, and root mean square errors, Pearson’s correlation coefficients, intraclass correlation coefficients, and the Bland Altman method were used to compare kinematic variables of interest between the two systems for absolute accuracy and equivalency. The T’ena sensor and the gold standard reference system were significantly correlated for all tasks and measures (r range = 0.648—0.947), although less so for the Finger to Nose task (r range = 0.648—0.894). Results demonstrate that single IMU systems are a valid, reliable, and objective method by which to measure movement kinematics during functional tasks. Context-appropriate enabling technologies specifically designed to address barriers to quality health services in LMICs can accelerate progress towards the United Nations Sustainable Development Goal 3.

Upper limb movement quality measures: comparing IMUs and optical motion capture in stroke patients performing a drinking task

“…Furthermore, when considering the applicability of our methods to other movement tasks, existing research indicates that errors similar to those we reported for upper limb movements in the drinking task are likely to be observed ( 22 , 33 , 24 , 23 ). Therefore, we anticipate our methodology will yield consistent error margins across various upper limb activities, assuming they do not significantly diverge from the movements studied in our drinking task research.…”

“…In terms of end-effector velocity during the drinking task with IMUs our study is the first one to test a kinematic model for this purpose. While our method allows for very high temporal resolution and reconstruction of end-effector velocity, the integration-based analysis used in a previous study on the drinking task reports even smaller RMSEs ( 23 ), but such an analysis might be vulnerable to sensor drift. Thus, a combination of both methods would likely yield the most robust and accurate results.…”

“…This evaluation should specifically focus on the measurement uncertainty of IMUs when determining the established movement quality measures in stroke patients with mild to moderate upper limb impairment. Three previous studies compared measurements from IMUs to OMC for the drinking task (22)(23)(24). However, none of these studies comprehensively investigated the full set of the mentioned movement quality measures among stroke patients.…”

Feasibility of Using a GENEActiv Accelerometer with Triaxial Acceleration and Temperature Sensors to Monitor Adherence to Shoulder Sling Wear Following Surgery

“…Objective assessment of sling treatment adherence has been previously attempted with temperature sensors incorporated in a sling to determine whether the sling is in contact with the body, i.e., is being worn [14]. Understandably, temperature change is gradual thus there was a time lag between temperature measured and the actual sling donning or doffing potentially impacting on the accuracy of monitoring of adherence to treatment [15].…”

Upper-Limb Kinematic Behavior and Performance Fatigability of Elderly Participants Performing an Isometric Task: A Quasi-Experimental Study

“…According to recent studies, IMU sensor systems accurately measure motor function and supply useful data concerning motor elements that promote assignment performance such as movement precision, smoothness, and accuracy [31], even in single IMU systems [32], showing encouraging results with respect to their reliability and intersystem agreement [33,34], especially in temporal parameters during activity [24] with higher validity for simple tasks [35].…”