Design and Implementation of an Instrumented Data Glove that measures Kinematics and Dynamics of Human Hand

Abstract

Human hands are versatile biomechanical architectures that can perform simple movements such as grasping to complicated movements such as playing a musical instrument. Such extremely dependable and useful parts of the human body can be debilitated due to movement disorders such as Parkinson’s disease, stroke, spinal cord injury, multiple sclerosis and cerebral palsy. In such cases, precisely measuring the residual or abnormal hand function becomes a critical assessment to help clinicians and physical therapists in diagnosis, treatment and in prescribing appropriate prosthetics or rehabilitation therapies. The current methodologies used to measure abnormal or residual hand function are either paperbased scales that are prone to human error or expensive motion tracking systems. The cost and complexity restrict the usability of these methods in clinical environments. In this paper we present a low-cost instrumented glove that can measure kinematics and dynamics of human hand, by leveraging the recent advances in 3D printing technologies and flexible sensors.