To develop a wearable device and investigate its feasibility to quantify fine motor movements in Parkinson’s Disease (PD) patients versus healthy controls.

The ability to objectively and efficiently assess fine motor movements can help not only with the diagnosis of PD but also to quantify symptom severity and monitor treatment efficacy.  A smart glove was developed with flex sensors capable of measuring the amplitude and frequency components of fine motor movements, such as tasks performed during a doctor’s visit for PD.

Using a smart glove to measure amplitude and frequency of fine motor movements was feasible in PD and control participants.  SVM classifier provided the most optimum results of 53.33% accuracy, with 87.29% and 19.38% for sensitivity and specificity, respectively.

The pilot study results demonstrate the feasibility of measuring motor function using a smart glove. However, the poor detection accuracy suggests that other measures of the finger tapping such as  frequency and amplitude of finger tapping, can improve the accuracy. However, other measures such as energy detection based on moving means and increased variances embedded in the signal should be investigated in the detection and analysis algorithms. This requires further testing in larger groups.