Eleonora Guanziroli1,2, Maurizio Cazzaniga3, Laura Colombo3, Sabrina Basilico3, Giovanni Legnani4, Franco Molteni3. 1. Villa Beretta Rehabilitation Center, Valduce Hospital, Costa Masnaga, Lecco, Italy - eleonora.guanziroli@gmail.com. 2. Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy - eleonora.guanziroli@gmail.com. 3. Villa Beretta Rehabilitation Center, Valduce Hospital, Costa Masnaga, Lecco, Italy. 4. Department of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy.
Abstract
BACKGROUND: Wearable powered robotic exoskeletons allow patients with complete spinal cord injury (SCI) to practice over-ground real-world gait scenarios. The global functional interaction subject-exoskeleton is a key factor to produce interlimb coordinated movements. Efficacy and efficiency of over-ground walking abilities using powered exoskeletons are related not only to the symbiotic sensory-motor interaction subject-exoskeleton but also to exoskeleton control. AIM: Assess if walking ability of motor complete SCI patients at thoracic or lower level, using a wearable powered exoskeleton (ReWalk), can be influenced by different exoskeleton software control. DESIGN: Observational study; an open, non-comparative, non-randomized study. SETTING: A single neurological rehabilitation center for inpatients and outpatients. POPULATION: Fifteen SCI chronic patients (4 females and 11 males) were recruited and divided in two groups: group 1, trained with the first software generation of ReWalk, and group 2, trained with the second software generation, a software upgrade of the previous version. METHODS: Subjects were trained during three 60-minute sessions a week, during at least eight weeks using ReWalk, a wearable lower limb powered exoskeleton that allows thoracic or lower level motor-complete individuals with SCI to walk, stand, sit and climb/descend stairs. Outcome measures, collected at the end of the training period wearing the exoskeleton, were: 6-min Walking Test, 10-m Walking Test, and the time necessary to pass from sitting to standing and start to walk (STS-time). For each group Pearson Coefficient was calculated to explore correlations between the subjects' characteristics and gait performance reached at the end of the training period. RESULTS: Group 1 showed correlation between performances and weight, height, neurological lesion level, while group 2 showed no correlation between performances weight and height, but correlation only with neurological lesion level. Group 2 covered more distance in 6 min (+124.52%) and required less time (-70.34%) to perform 10 mtWT and to STS-time (-38.25%) if compared to group 1. CONCLUSIONS: ReWalk allows chronic complete spinal cord injury patients to perform over-ground walking. Different exoskeleton software control of the smoothness of the gait pattern improves functional outcome, eliminating the relationship between anthropometric factors and gait performances. The smoothness of the kinematic control of the lower limbs of the exoskeleton is a key factor to facilitate human-robot interaction and to increase walking abilities of the subject. CLINICAL REHABILITATION IMPACT: To underline how the kinematic control of the exoskeleton influences the walking abilities of the complex system subject-exoskeleton.
BACKGROUND: Wearable powered robotic exoskeletons allow patients with complete spinal cord injury (SCI) to practice over-ground real-world gait scenarios. The global functional interaction subject-exoskeleton is a key factor to produce interlimb coordinated movements. Efficacy and efficiency of over-ground walking abilities using powered exoskeletons are related not only to the symbiotic sensory-motor interaction subject-exoskeleton but also to exoskeleton control. AIM: Assess if walking ability of motor complete SCI patients at thoracic or lower level, using a wearable powered exoskeleton (ReWalk), can be influenced by different exoskeleton software control. DESIGN: Observational study; an open, non-comparative, non-randomized study. SETTING: A single neurological rehabilitation center for inpatients and outpatients. POPULATION: Fifteen SCI chronic patients (4 females and 11 males) were recruited and divided in two groups: group 1, trained with the first software generation of ReWalk, and group 2, trained with the second software generation, a software upgrade of the previous version. METHODS: Subjects were trained during three 60-minute sessions a week, during at least eight weeks using ReWalk, a wearable lower limb powered exoskeleton that allows thoracic or lower level motor-complete individuals with SCI to walk, stand, sit and climb/descend stairs. Outcome measures, collected at the end of the training period wearing the exoskeleton, were: 6-min Walking Test, 10-m Walking Test, and the time necessary to pass from sitting to standing and start to walk (STS-time). For each group Pearson Coefficient was calculated to explore correlations between the subjects' characteristics and gait performance reached at the end of the training period. RESULTS: Group 1 showed correlation between performances and weight, height, neurological lesion level, while group 2 showed no correlation between performances weight and height, but correlation only with neurological lesion level. Group 2 covered more distance in 6 min (+124.52%) and required less time (-70.34%) to perform 10 mtWT and to STS-time (-38.25%) if compared to group 1. CONCLUSIONS: ReWalk allows chronic complete spinal cord injurypatients to perform over-ground walking. Different exoskeleton software control of the smoothness of the gait pattern improves functional outcome, eliminating the relationship between anthropometric factors and gait performances. The smoothness of the kinematic control of the lower limbs of the exoskeleton is a key factor to facilitate human-robot interaction and to increase walking abilities of the subject. CLINICAL REHABILITATION IMPACT: To underline how the kinematic control of the exoskeleton influences the walking abilities of the complex system subject-exoskeleton.
Authors: Xiao-Na Xiang; Hui-Yan Zong; Yi Ou; Xi Yu; Hong Cheng; Chun-Ping Du; Hong-Chen He Journal: J Neuroeng Rehabil Date: 2021-05-24 Impact factor: 4.262
Authors: Arvind Ramanujam; Kamyar Momeni; Manikandan Ravi; Jonathan Augustine; Erica Garbarini; Peter Barrance; Ann M Spungen; Pierre Asselin; Steven Knezevic; Gail F Forrest Journal: Front Robot AI Date: 2020-12-09