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While falls among patients with mild cognitive impairment (MCI) have been closely associated with an increased postural sway during ecological activities of daily living, there is a dearth of postural sway detection (PSD) research in ecological environments. The present study aimed to investigate the fall sensitivity, specificity, and accuracy of our PSD system. Forty healthy young and older adults with MCI at a high risk of falls underwent the sensitivity, specificity, and accuracy tests for PSD by simultaneously recording the Berg Balance Scale and Timed Up and Go in ecological environments, and the data were analyzed using the receiver operating characteristic curve and area under the curve. The fall prediction sensitivity ranged from 0.82 to 0.99, specificity ranged from 0.69 to 0.90, and accuracy ranged from 0.53 to 0.81. The PSD system’s fall prediction sensitivity, specificity, and accuracy data suggest a reasonable discriminative capacity for distinguishing between fallers and non-fallers as well as predicting falls in older adults with MCI in ecological testing environments.

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Robot-assisted gait training (RAGT) is a promising therapeutic vehicle to maximize active participation and enhance functional neuroplasticity in patients with central nervous system pathology by adequately adjusting gait speed, body weight support (BWS) level, and impedance provided by the exoskeleton. The aim of the present study was to determine the relationship between RAGT training parameters (BWS and speed) and electromyography (EMG) muscle activity torques in the knee and hip joint during RAGT. To analyze the correlation between the joint torques measured in the Walkbot gait rehabilitation system and the EMG signal of the lower limbs (vastus lateralis oblique, biceps femoris, tibialis anterior, and gastrocnemius) and understand the real-time state of the lower limb an experiment involving 20 subjects was conducted. The EMG–torque relationship was evaluated in a general rehabilitation training setting to overcome the limitations of in vivo settings. Pearson correlation coefficient analysis was performed at p < 0.05. Moderate relationships between biceps femoris activation data and hip and knee torques were statistically significant, ranging from r = 0.412 to −0.590, p < 0.05). Importantly, inverse relationships existed between hip torques and vastus lateralis oblique, biceps femoris, and tibialis anterior activation, respectively. The present results demonstrated the association between EMG locomotor control patterns and torque generation in the hip and knee joints during RAGT-treadmill under the different BWS and walking speed settings while adjusting the impedance mode parameters in non-neurological adults. Additionally, the EMG locomotor control patterns, concurrent torque generation in the hip and knee joints, and application of different BWS and walking speed parameters in the RAGT were linked to the gait speed and BWS. The outcomes also showed that the amount of BWS supplied had an impact on the effects of treadmill speed on muscle activity and temporal step control. It is essential to adjust RAGT parameters precisely in order to maximize training session efficiency and quality. The results of this study nevertheless call for more investigation into the relationship between muscle activity and torque outcomes in diseased populations with gait impairment.