A novel gait analysis system for detecting abnormal hemiparetic gait patterns during robot-assisted gait training: A criterion validity study among healthy adults

Abstract

IntroductionRobot-assisted gait training has been reported to improve gait in individuals with hemiparetic stroke. Ideally, the gait training program should be customized based on individuals’ gait characteristics and longitudinal changes. However, a gait robot that uses gait characteristics to provide individually tailored gait training has not been proposed. The new gait training robot, “Welwalk WW-2000,” permits modification of various parameters, such as time and load of mechanical assistance for a patient’s paralyzed leg. The robot is equipped with sensors and a markerless motion capture system to detect abnormal hemiparetic gait patterns during robot-assisted gait training. Thus, it can provide individually tailored gait training. This study aimed to investigate the criterion validity of the gait analysis system in the Welwalk WW-2000 in healthy adults.Materials and methodsTwelve healthy participants simulated nine abnormal gait patterns that were often manifested in individuals with hemiparetic stroke while wearing the robot. Each participant was instructed to perform a total of 36 gait trials, with four levels of severity for each abnormal gait pattern. Fifteen strides for each gait trial were recorded using the markerless motion capture system in the Welwalk WW-2000 and a marker-based three-dimensional (3D) motion analysis system. The abnormal gait pattern index was then calculated for each stride from both systems. The correlation of the index values between the two methods was evaluated using Spearman’s rank correlation coefficients for each gait pattern in each participant.ResultsUsing the participants’ index values for each abnormal gait pattern obtained using the two motion analysis methods, the median Spearman’s rank correlation coefficients ranged from 0.68 to 0.93, which corresponded to moderate to very high correlation.ConclusionThe gait analysis system in the Welwalk WW-2000 for real-time detection of abnormal gait patterns during robot-assisted gait training was suggested to be a valid method for assessing gait characteristics in individuals with hemiparetic stroke.Clinical trial registration[https://jrct.niph.go.jp], identifier [jRCT 042190109].

Gait Analysis in Neurorehabilitation: From Research to Clinical Practice

“…Other kinds of wearable devices used in neurorehabilitation motor training include robotics (i.e., end-effectors and/or exoskeletons), which could be used to automatically perform a sort of gait analysis to register the improvements before and after the training in spatial-temporal, kinematic, and kinetic parameters of gait. Imoto et al [66] developed a new and valid gait training robot named Welwalk WW-2000 (WW-2000, Toyota Motor Corporation, Aichi, Japan), which is equipped with sensors and a marker-less motion capture system for hemiparetic individuals. The robot can register a patient's gait parameters and provide tailored gait training, adapting to the patient's gait characteristics.…”

Robot-Aided Motion Analysis in Neurorehabilitation: Benefits and Challenges

“…A possible solution could involve the use of robotic devices in which the patient would undergo both training and assessment. In this study, Imoto et al [46] used a novel gait training robot known as WelWalk WW-2000. This robot enables the adjustment of various gait parameters (such as time and mechanical assistance load) during the training session.…”

“…The robot is equipped with sensors and a markerless motion capture system to detect altered gait patterns in stroke patients. This system can evaluate individuals' gait patterns and provide tailored rehabilitation gait training [46]. Generally, the objective assessment of the lower limb should consider the simultaneous measurement of joint angles, spatial and temporal parameters of gait, muscle strength, proprioception, and spasticity and/or muscle stiffness [47] (see Table 2).…”

“…Usefulness of Robot-Aided Motion Analysis [46] WelWalk (WW-2000, Toyota Motor Corporation, Aichi, Japan) Knee-ankle-foot robot, low floor treadmill, safety suspension device for body weight support, monitor for patient use, 3D sensor, and control panel Three-dimensional joint positions, lower limb tilt, and knee joint angle were recorded during a task using a 3D sensor, an inertial sensor, and a knee angle sensor. Two-dimensional joint positions collected using skeletal tracking software (VisionPose ® , NEXT-SYSTEM Co., Ltd., Fukuoka, Japan) and depth data from the 3D sensor were used to estimate the three-dimensional coordinates of the joint positions.…”

Cluster Analysis of Subjective Shoulder Stiffness and Muscle Hardness: Associations with Central Sensitization-Related Symptoms

“…Posture alignment was analyzed using the VisionPose application, which employs deep learning for posture estimation. VisionPose is utilized to measure postural alignment [28]. The spinal angle and head position were calculated as postural alignment indicators during quiet sitting.…”