Gait analysis system for assessing abnormal patterns in individuals with hemiparetic stroke during robot-assisted gait training: a criterion-related validity study in healthy adults

 Assessments do nothing unless they are directly followed by EXACT PROTOCOLS THAT DELIVER RECOVERY! I'd have you all fired!

Gait analysis system for assessing abnormal patterns in individuals with hemiparetic stroke during robot-assisted gait training: a criterion-related validity study in healthy adults

Issei Nakashima^1,2Daisuke Imoto³Satoshi Hirano^1*Hitoshi Konosu^2,4Yohei Otaka¹

• ¹Department of Rehabilitation Medicine, School of Medicine, Fujita Health University, Aichi, Japan
• ²Toyota Motor Corporation, Aichi, Japan
• ³Department of Rehabilitation, Fujita Health University Hospital, Aichi, Japan
• ⁴Department of Rehabilitation Medicine, Graduate School of Medicine, Fujita Health University, Aichi, Japan

Introduction: Gait robots have the potential to analyze gait characteristics during gait training using mounted sensors in addition to robotic assistance of the individual’s movements. However, no systems have been proposed to analyze gait performance during robot-assisted gait training. Our newly developed gait robot,” Welwalk WW-2000 (WW-2000)” is equipped with a gait analysis system to analyze abnormal gait patterns during robot-assisted gait training. We previously investigated the validity of the index values for the nine abnormal gait patterns. Here, we proposed new index values for four abnormal gait patterns, which are anterior trunk tilt, excessive trunk shifts over the affected side, excessive knee joint flexion, and swing difficulty; we investigated the criterion validity of the WW-2000 gait analysis system in healthy adults for these new index values.

Methods: Twelve healthy participants simulated four abnormal gait patterns manifested in individuals with hemiparetic stroke while wearing the robot. Each participant was instructed to perform 16 gait trials, with four grades of severity for each of the four abnormal gait patterns. Twenty strides were recorded for each gait trial using a gait analysis system in the WW-2000 and video cameras. Abnormal gait patterns were assessed using the two parameters: the index values calculated for each stride from the WW-2000 gait analysis system, and assessor’s severity scores for each stride. The correlation of the index values between the two methods was evaluated using the Spearman rank correlation coefficient for each gait pattern in each participant.

Results: The median (minimum to maximum) values of Spearman rank correlation coefficient among the 12 participants between the index value calculated using the WW-2000 gait analysis system and the assessor’s severity scores for anterior trunk tilt, excessive trunk shifts over the affected side, excessive knee joint flexion, and swing difficulty were 0.892 (0.749–0.969), 0.859 (0.439–0.923), 0.920 (0.738–0.969), and 0.681 (0.391–0.889), respectively.

Discussion: The WW-2000 gait analysis system captured four new abnormal gait patterns observed in individuals with hemiparetic stroke with high validity, in addition to nine previously validated abnormal gait patterns. Assessing abnormal gait patterns is important(You're completely and totally wrong here!) as improving them contributes to stroke rehabilitation.

Clinical trial registration: https://jrct.niph.go.jp, identifier jRCT 042190109.

1 Introduction

Improving gait of individuals with hemiparetic stroke through gait training is the primary goal for stroke rehabilitation (Jette et al., 2005; Latham et al., 2005). Robot-assisted gait training (RAGT) has been proposed as a method for improving the gait of individuals with hemiparetic stroke (Mehrholz et al., 2020), as it can provide intensive, repetitive, task-oriented training for those who are unable to walk independently by partially or fully supporting their weight and movements with a robot control mechanism (Morone et al., 2017). According to systematic reviews, RAGT in individuals with hemiparetic stroke is particularly effective in achieving walking independence (Mehrholz et al., 2020), and its use is recommended in treatment guidelines (Calabrò et al., 2021).

Appropriate assessment of gait characteristics in individuals with hemiparetic stroke is useful for planning treatment goals (Mulroy et al., 2003), monitoring treatment effects (Toro et al., 2003), and predicting the degree of improvement (Kaczmarczyk et al., 2012). Therefore, an important component for maximizing the effectiveness of RAGT is the appropriate assessment of the individual’s gait characteristics during gait training. Observational gait analysis is generally used in clinical practice to analyze gait characteristics (Perry et al., 2010). In contrast, the gait analysis method using a three-dimensional (3D) gait analysis device can acquire objective information, such as temporal and spatial parameters (Baker, 2006). Gait robots have the potential to contribute to quantitatively analyze gait characteristics using mounted sensors; however, no systems have been proposed to analyze gait performance during RAGT.

We developed a new gait training robot with a markerless motion capture system, Welwalk WW-2000 (WW-2000, Toyota Motor Corporation, Aichi, Japan), which enables measurement of various parameters, including time and mechanical assistance load, of an individual’s paralyzed leg. This gait robot system analyzes abnormal hemiparetic gait patterns during RAGT using various sensors (Nakashima et al., 2020). We previously proposed the following index values of nine abnormal gait patterns: hip hiking, circumduction, retropulsion of the hip, excessive hip external rotation, excessive lateral shift of the trunk over the unaffected side, knee extensor thrust, medial whip, posterior trunk tilt, and contralateral vaulting. The index values are highly correlated with those of abnormal gait patterns analyzed using an existing marker-based 3D motion capture system, indicating criterion-related validity (Imoto et al., 2022). In addition to the nine previously reported abnormal gait patterns, the WW-2000 gait analysis system can analyze index values for four more abnormal gait patterns frequently observed in individuals with hemiparetic stroke: anterior trunk tilt (Olney and Richards, 1996), excessive trunk shifts over the affected side (Carr and Shepherd, 1987), excessive knee joint flexion (de Quervain et al., 1996), and swing difficulty (Burpee and Lewek, 2015). There are no reports of objective index values using an existing marker-based 3D motion capture system for these abnormal gait patterns. However, these patterns may lead to unstable walking, decreased walking speed, and a reduced walking endurance in individuals with hemiparetic stroke. Therefore, we needed to examine the validity of the index values analyzed by the WW-2000 gait analysis system using a different research design than that of a previous study (Imoto et al., 2022). The validity of the index values for abnormal gait patterns calculated by the WW-2000 gait analysis system will be comprehensively clarified through the previous study and present study. Consequently, we expect that this gait analysis system will enable the comprehensive assessment for abnormal gait patterns that occur in individuals with hemiparetic stroke during RAGT with quantitative indicators, thereby contributing to the improvement of abnormal gait patterns.

Overall, this study aimed to propose new index values for the four abnormal gait patterns that occur during RAGT, and to clarify the criterion-related validity of the index values of the four new abnormal gait patterns calculated using the WW-2000 gait analysis system: anterior trunk tilt, excessive trunk shifts over the affected side, excessive knee joint flexion, and swing difficulty, in addition to the nine previously reported abnormal gait patterns.

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