Gait performance and foot pressure distribution during wearable robot-assisted gait in elderly adults

Su-Hyun Lee, Hwang-Jae Lee, Won Hyuk Chang, Byung-Ok Choi, Jusuk Lee, Jeonghun Kim, Gyu-Ha Ryu, Yun-Hee Kim, Su-Hyun Lee, Hwang-Jae Lee, Won Hyuk Chang, Byung-Ok Choi, Jusuk Lee, Jeonghun Kim, Gyu-Ha Ryu, Yun-Hee Kim

Abstract

Background: A robotic exoskeleton device is an intelligent system designed to improve gait performance and quality of life for the wearer. Robotic technology has developed rapidly in recent years, and several robot-assisted gait devices were developed to enhance gait function and activities of daily living in elderly adults and patients with gait disorders. In this study, we investigated the effects of the Gait-enhancing Mechatronic System (GEMS), a new wearable robotic hip-assist device developed by Samsung Electronics Co, Ltd., Korea, on gait performance and foot pressure distribution in elderly adults.

Methods: Thirty elderly adults who had no neurological or musculoskeletal abnormalities affecting gait participated in this study. A three-dimensional (3D) motion capture system, surface electromyography and the F-Scan system were used to collect data on spatiotemporal gait parameters, muscle activity and foot pressure distribution under three conditions: free gait without robot assistance (FG), robot-assisted gait with zero torque (RAG-Z) and robot-assisted gait (RAG).

Results: We found increased gait speed, cadence, stride length and single support time in the RAG condition. Reduced rectus femoris and medial gastrocnemius muscle activity throughout the terminal stance phase and reduced effort of the medial gastrocnemius muscle throughout the pre-swing phase were also observed in the RAG condition. In addition, walking with the assistance of GEMS resulted in a significant increase in foot pressure distribution, specifically in maximum force and peak pressure of the total foot, medial masks, anterior masks and posterior masks.

Conclusion: The results of the present study reveal that GEMS may present an alternative way of restoring age-related changes in gait such as gait instability with muscle weakness, reduced step force and lower foot pressure in elderly adults. In addition, GEMS improved gait performance by improving push-off power and walking speed and reducing muscle activity in the lower extremities.

Trial registration: NCT02843828 .

Keywords: Elderly adults; Foot pressure distribution; Gait; Muscle activity; Spatiotemporal gait parameters; Wearable hip-assist robot.

Conflict of interest statement

Ethics approval and consent to participate

All procedures in this study were approved by the ethics committee of the Samsung Medical Center Institutional Review Board and were consistent with the Declaration of Helsinki. Written consent to participate in the experiment was obtained from all subjects recruited through Samsung Medical Center.

Consent for publication

The individual in Fig. 1 a consented to the publication of the photograph.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
a Gait-enhancing Mechatronic System (GEMS). b Segmented foot regions on the insole. T1 1st toe, T2 2nd toe, T3 3rd toe, T45 4th–5th toes, M1 1st metatarsal, M2 2nd metatarsal, M3 3rd metatarsal, M4 4th metatarsal, M5 5th metatarsal, MH medial heel, LH lateral heel
Fig. 2
Fig. 2
Device left and right joint angle, estimated gait cycle for each joint, and desired left and right joint torque. Positive value is the flexion
Fig. 3
Fig. 3
Average EMG activity (%MVC) of measured muscles during one gait cycle. a Average sEMG activity of rectus femoris during one gait cycle. b Average sEMG activity of biceps femoris during one gait cycle. c Average sEMG activity of tibialis anterior during one gait cycle. d Average sEMG activity of medial gastrocnemius during one gait cycle. FG free gait without robot assistance, RAG-Z robot-assisted gait with zero torque, RAG robot-assisted gait, sEMG surface electromyography, MVC maximum voluntary contraction

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