Assessing upper extremity motor function in practice of virtual activities of daily living.

A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user's avatar and automated generation of metrics related to speed and smoothness of motion.

Withdrawal reflexes in the upper limb adapt to arm posture and stimulus location.

Introduction: Withdrawal reflexes in the leg adapt in a context-appropriate manner to remove the limb from noxious stimuli, but the extent to which withdrawal reflexes adapt in the arm remains unknown.

Methods: We examined the adaptability of withdrawal reflexes in response to nociceptive stimuli applied in different arm postures and to different digits. Reflexes were elicited at rest, and kinetic and electromyographic responses were recorded under isometric conditions, thereby allowing motorneuron pool excitability to be controlled.

Optimal input selection for neural machine interfaces predicting multiple non-explicit outputs.

This study implemented a novel algorithm that optimally selects inputs for neural machine interface (NMI) devices intended to control multiple outputs and evaluated its performance on systems lacking explicit output. NMIs often incorporate signals from multiple physiological sources and provide predictions for multidimensional control, leading to multiple-input multiple-output systems. Further, NMIs often are used with subjects who have motor disabilities and thus lack explicit motor outputs.