Development and evaluation of a low-cost sensor glove for assessment of human finger movements in neurophysiological settings

Sensor gloves for measurements of finger movements are a promising tool for objective assessments of kinematic parameters and new rehabilitation strategies. Here, a novel low-cost sensor glove equipped with resistive bend sensors is described and evaluated. Resistive bend sensors were modified in order to optimize measurement accuracy (quantified as the stability of sensor signal after a fast and constant bending) and to increase sensor linearity, reducing calibration time from several minutes to only ∼10 s. Reliability analysis of the sensor glove in five subjects showed an intraclass correlation coefficient (ICC) of 0.93 ± 0.05, a mean standard deviation of 1.59° and an overall error of 4.96°, comparable to previously evaluated sensor gloves. User acceptance and applicability, assessed by a user feedback questionnaire, was high. Thus, with minor modifications, resistive bend sensors are suitable for accurate assessments of human finger movements. The low material costs (