Real-time biofeedback device for gait rehabilitation of post-stroke patients

Abstract

In this work, we develop a device, called 'Walk-Even', that can provide real-time feedback to correct gait asymmetry commonly exhibited in post-stroke survivors and persons with certain neurological disorders. The device computes gait parameters, including gait time, swing time, and stance time of each leg, to detect gait asymmetry and provide corresponding real-time biofeedback by means of auditory and electrotactile stimulation to actively correct the user's gait. The system consists of customized force-sensor-embedded insoles adjustable to fit any shoe size, electrotactile and auditory feedback circuits, microcontroller, and wireless XBee transceivers. The device also offers data saving capability. To validate its accuracy and reliability, we compared the gait measurements from our device with a commercial gait and balance assessment device, Zeno Walkway. The results show good correlation and agreement in a validity study with six healthy subjects and reliability study with seventeen healthy subjects. In addition, preliminary testing on six post-stroke patients after an 8-week training shows that the Walk-Even device helps to improve gait symmetry, foot pressure and forefoot loading of the affected side. Thus, initial testing indicates that the device is accurate in measuring the gait parameters and effective in improving gait symmetry using real-time feedback. The device is portable and low cost and has the potential for use in a non-clinical setting for patients that can walk independently without assistance. A more extensive testing with stroke patients is still ongoing.

Keywords: Biofeedback; Gait asymmetry; Rehabilitation; Stroke.

Fig. 1

Block diagram of device

Fig. 2

Device component placement on patient

Fig. 3

Flowcharts describing a Swing Feedback, b Stance Feedback

Fig. 4

a Sandals with custom force sensing insoles. b Locations of FSRs on the insole

Fig. 5

Force sensor interface circuit

Fig. 6

Boost converter circuit

Fig. 7

Output voltage across a 500 Ω test load at 80 μs pulse width

Fig. 8

Graphical user interface running on PC

Fig. 9

Complete device circuitry

Fig. 10

Walk-Even device worn by a post-stroke patient during the training

Fig. 11

Sample force readings in pounds recorded by the device for the left leg (red heel, blue toe). (Color figure online)

Fig. 12

Gait parameters calculation using predetermined thresholds

Fig. 13

Bland–Altman plots for normal walking condition: a gait time, b swing time, c stance time

Fig. 14

Bland–Altman plots for asymmetric walking condition: a gait time, b swing time, c stance time

Fig. 15

Asymmetry ratio progression (with SD error bars) for six test subjects. Subjects 1 and 2 receive Stance Feedback, subjects 3 and 4 receive Swing Feedback, subjects 5 and 6 are Control

Fig. 16

Affected side foot pressure for six test subjects, pre- and post-intervention measured with Tekscan F-scan

Fig. 17

Sample of heel and metatarsal (forefoot) forces of the affected side across the normalized gait cycle, pre- and post-intervention of one subject measured with Tekscan F-scan

Fig. 18

Heel to forefoot transfer points for the six subjects, pre- and post-intervention measured with Tekscan F-scan. Note that the lesser values in post-intervention indicate earlier transfer of body weight from heel to forefoot