[ARTICLE] Improved walking ability with wearable robot-assisted training in patients suffering chronic stroke – OPEN ACCESS

Abstract

Wearable robotic devices provide safe and intensive rehabilitation, enabling repeated motions for motor function recovery in stroke patients.

The aim of this small case series was to demonstrate the training effects of a three-week robotic leg orthosis, and to investigate possible mechanisms of the sensory-motor alterations and improvements by using gait analysis and EMG.

Three survivors of chronic strokes participated in robot-assisted gait therapy for three weeks. EMG signals from the rectus femoris (RF), tibialis anterior (TA), biceps femoris (BF), and medial gastrocnemius (MG), as well as kinetics and kinematics data of the lower limb, were recorded before and after the training. The normalized root mean squared (RMS) values of the muscles, the joint moments, joint angles, and the results of two clinical scales (Berg Balance scale, BBS, and the lower extremity subscale of Fugl-Meyer assessment, LE-FMA) were used for analysis. All participants experienced improved balance and functional performances and increased BBS and LE-FMA scores.

The EMG results showed there was an increase of the normalized RMS values of the MG and BF on the affected side. Additionally, EMG activities of the agonist and antagonist pair (i.e. RF and BF) appeared to return to similar levels after training. The peak moment of hip flexor, knee extensor, and plantar flexor, which all contributed to push-off power, were found to have increased after training.

In summary, the three-week training period using the wearable RLO improved the three participants’ gait performance by regaining push-off power and improved muscle activation and walking speed.

Full Text PDF

, , , , , ,

  1. Leave a comment

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: