Assessment of ranges of rest postures of human lower limbs

Effects of kinesio taping on neck-shoulder discomfort and EMG responses during smartphone texting in healthy young adults

BACKGROUND

While kinesio taping (KT) is used in several clinical settings to correct posture and reduce pain, KT effects during smartphone texting are unknown.

OBJECTIVE

To investigate the effects among healthy young adults of KT on neck-shoulder discomfort and electromyographic (EMG) responses of neck and upper trunk muscles during smartphone texting.

METHODS

Twenty-four participants performed a 30-minute texting task on a smartphone using both hands at two separate times under one of two conditions: KT on the right shoulder and no taping. Neck-shoulder discomfort was assessed, along with the normalized root mean square (NRMS) and normalized median frequency (NMF) of the right cervical erector spinae (CES), lower trapezius (LT), and serratus anterior (SA).

RESULTS

Compared to baseline, both groups had significantly greater neck-shoulder discomfort, and NRMS and NMF of all muscles (p < 0.001) after performing a 30-minute texting task. Comparing between groups, the KT group experienced significantly less neck-shoulder discomfort, and demonstrated delayed deterioration of NRMS and NMF of right CES and LT muscles (p < 0.05).

CONCLUSIONS

During smartphone texting, KT on the shoulder decreased neck-shoulder discomfort and delayed reduction of activation and fatigue of neck and upper trunk muscles among healthy young adults.

A reach motion generation algorithm based on posture memories

BACKGROUND

Most existing models/algorithms for simulating goal-directed human motions were designed to generate a single "realistic" motion for a given input scenario.

OBJECTIVE

This study presents a novel reach motion generation algorithm utilizing multiple posture memories. The algorithm aims to compute and visualize a set of human reach motions that approximates the full range of physically and physiologically feasible human motions for a given input scenario.

METHODS

The algorithm utilizes posture memories constructed specifically for an individual worker using a probabilistic posture generation and registration process. The posture memories relate a hand position to the set of postures that place the individual's hand in its vicinity. When given an input scenario, the algorithm first generates different hand paths connecting the starting and ending hand positions specified in the scenario. Then, for each hand path, the algorithm produces different "feasible" motions by selecting and connecting multiple postures stored in the posture memories; the postures corresponding to the hand positions along the hand path are utilized.

CONCLUSIONS

The proposed algorithm helps understand the impacts of workplace design on the range of feasible human motion behaviors, and, thereby, contributes to the computer-aided ergonomics design of work tasks and workplaces.