Ankle dorsiflexion assistance of patients with foot drop using a powered ankle-foot orthosis to improve the gait asymmetry.

BACKGROUND: Foot drop is a neuromuscular disorder that causes abnormal gait patterns. This study developed a pneumatically powered ankle-foot orthosis (AFO) to improve the gait patterns of patients with foot drop. We hypothesized that providing unilateral ankle dorsiflexion assistance during the swing phase would improve the kinematics and spatiotemporal gait parameters of such patients. Accordingly, this study aims to examine the efficacy of the proposed assistance system using a strategy for joint kinematics and spatiotemporal gait parameters (stride length, swing velocity, and stance phase ratio). The analysis results are expected to provide knowledge for better design and control of AFOs in patients with foot drop. METHOD: Ten foot drop patients with hemiparesis (54.8 y ± 14.1 y) were fitted with a custom AFO with an adjustable calf brace and portable air compressor for ankle dorsiflexion assistance in the gait cycle during the swing phase. All subjects walked under two different conditions without extensive practice: (1) barefoot and (2) wearing a powered AFO. Under each condition, the patients walked back and forth on a 9-m track with ten laps of level ground under the supervision of licensed physical therapists. The lower-limb joint and trunk kinematics were acquired using 12 motion-capture cameras. RESULTS: We found that kinematic asymmetry decreased in the three lower-limb joints after ankle dorsiflexion assistance during the swing phase. The average ankle-joint angle increased after using the AFO during the entire gait cycle. Similarly, the knee-joint angle showed a slight increase while using the AFO, leading to a significantly decreased standard deviation within patients. Conversely, the hip-joint angle showed no significant improvements with assistance. While several patients exhibited noticeably lower levels of asymmetry, no significant changes were observed in the average asymmetry of the swing velocity difference between the affected and unaffected sides while using the AFO. CONCLUSION: We experimentally validated that ankle dorsiflexion assistance during the swing phase temporarily improves gait asymmetry in foot-drop patients. The experimental results also prove the efficacy of the developed AFO for gait assistance in foot-drop patients.

Kinematic Assessment to Measure Change in Impairment during Active and Active-Assisted Type of Robotic Rehabilitation for Patients with Stroke.

Analysis of kinematic features related to clinical assessment scales may qualitatively improve the evaluation of upper extremity movements of stroke patients. We aimed to investigate kinematic features that could correlate the change in the Fugl-Meyer Assessment (FMA) score of stroke survivors through upper extremity robotic rehabilitation. We also analyzed whether changes in kinematic features by active and active-assisted robotic rehabilitation correlated differently with changes in FMA scores. Fifteen stroke patients participated in the upper extremity robotic rehabilitation program, and nine kinematic features were calculated from reach tasks for assessment. Simple and multiple linear regression analyses were used to characterize correlations. Features representing movement speed were associated with changes in FMA scores for the group that used an active rehabilitation robot. In contrast, in the group that used an active-assisted rehabilitation robot, features representing movement smoothness were associated with changes in the FMA score. These estimates can be an important basis for kinematic analysis to complement clinical scales.

A comparison of the effects and usability of two exoskeletal robots with and without robotic actuation for upper extremity rehabilitation among patients with stroke: a single-blinded randomised controlled pilot study.

BACKGROUND: Robotic rehabilitation of stroke survivors with upper extremity dysfunction may yield different outcomes depending on the robot type. Considering that excessive dependence on assistive force by robotic actuators may interfere with the patient's active learning and participation, we hypothesised that the use of an active-assistive robot with robotic actuators does not lead to a more meaningful difference with respect to upper extremity rehabilitation than the use of a passive robot without robotic actuators. Accordingly, we aimed to evaluate the differences in the clinical and kinematic outcomes between active-assistive and passive robotic rehabilitation among stroke survivors. METHODS: In this single-blinded randomised controlled pilot trial, we assigned 20 stroke survivors with upper extremity dysfunction (Medical Research Council scale score, 3 or 4) to the active-assistive robotic intervention (ACT) and passive robotic intervention (PSV) groups in a 1:1 ratio and administered 20 sessions of 30-min robotic intervention (5 days/week, 4 weeks). The primary (Wolf Motor Function Test [WMFT]-score and -time: measures activity), and secondary (Fugl-Meyer Assessment [FMA] and Stroke Impact Scale [SIS] scores: measure impairment and participation, respectively; kinematic outcomes) outcome measures were determined at baseline, after 2 and 4 weeks of the intervention, and 4 weeks after the end of the intervention. Furthermore, we evaluated the usability of the robots through interviews with patients, therapists, and physiatrists. RESULTS: In both the groups, the WMFT-score and -time improved over the course of the intervention. Time had a significant effect on the WMFT-score and -time, FMA-UE, FMA-prox, and SIS-strength; group × time interaction had a significant effect on SIS-function and SIS-social participation (all, p < 0.05). The PSV group showed better improvement in participation and smoothness than the ACT group. In contrast, the ACT group exhibited better improvement in mean speed. CONCLUSIONS: There were no differences between the two groups regarding the impairment and activity domains. However, the PSV robots were more beneficial than ACT robots regarding participation and smoothness. Considering the high cost and complexity of ACT robots, PSV robots might be more suitable for rehabilitation in stroke survivors capable of voluntary movement. Trial registration The trial was registered retrospectively on 14 March 2018 at ClinicalTrials.gov (NCT03465267).

Gait analysis in hemiplegic stroke survivors who used the one-arm motorized walker.

OBJECTIVE: A high number of stroke survivors experience limitations in balance and gait abilities. Thus, an improvement in gait ability is an important goal in the rehabilitation of hemiplegic stroke survivors. This study aimed to investigate the effect of using the one-arm motorized walker, a hemi-walker developed to assist hemiplegic stroke survivors in gait training and activities of daily living, on the improvement in gait ability in hemiplegic stroke survivors. METHODS: Eleven hemiplegic stroke survivors who met the inclusion criteria were included. The participants were instructed to walk thrice using traditional walking aids on a gait mat and then to walk thrice using the one-arm motorized walker. During each walk, spatiotemporal gait parameters, including velocity, cadence, step length, stride length, single support time, and double support time, were evaluated using a gait analysis system. RESULTS: Velocity and cadence significantly increased when the participants walked using the one-arm motorized walker compared to those who used traditional walking aids (p< 0.05), whereas double support time significantly decreased for both the more affected and less affected sides (p< 0.05). However, no significant difference was observed in terms of step length and single support time. CONCLUSION: The one-arm motorized walker may have a positive effect on the improvement of gait ability in hemiplegic stroke survivors. It can be an effective walking aid for hemiplegic stroke survivors who experience difficulties in independent walking.

Movement stability analysis of surface electromyography-based elbow power assistance.

The use of power assistive devices that use surface electromyography (SEMG) signals may be limited by the noisy nature of SEMG signals. The aim of this study was to investigate the variation in human movement stability while the amount of SEMG-based assistive power was changed. A robotic device provided a torque that was proportional to the torque estimated by SEMG for assisting human movements, and 12 volunteers participated in the elbow flexion experiments. The maximum finite-time Lyapunov exponent (MFTLE), the average logarithmic rate of the divergence of neighboring trajectories, and the variability of the kinematic data were used to quantify the stability of the assisted elbow movements. The stability provided by the MFTLE decreased as the amount of assistive torque increased with respect to the amount of human torque. The kinematic variability increased with the increase in assistive torque. Therefore, by ensuring that the amount of SEMG-based assistive torque is less than the amount of human torque, the assistance may provide relatively natural movements. This study is the first to quantify movement stability as SEMG-based assistive power is applied. This study can provide a foundation for determining the appropriate amount of SEMG-based assistive power.

A practical strategy for sEMG-based knee joint moment estimation during gait and its validation in individuals with cerebral palsy.

Individuals with cerebral palsy have neurological deficits that may interfere with motor function and lead to abnormal walking patterns. It is important to know the joint moment generated by the patient's muscles during walking in order to assist the suboptimal gait patterns. In this paper, we describe a practical strategy for estimating the internal moment of a knee joint from surface electromyography (sEMG) and knee joint angle measurements. This strategy requires only isokinetic knee flexion and extension tests to obtain a relationship between the sEMG and the knee internal moment, and it does not necessitate comprehensive laboratory calibration, which typically requires a 3-D motion capture system and ground reaction force plates. Four estimation models were considered based on different assumptions about the functions of the relevant muscles during the isokinetic tests and the stance phase of walking. The performance of the four models was evaluated by comparing the estimated moments with the gold standard internal moment calculated from inverse dynamics. The results indicate that an optimal estimation model can be chosen based on the degree of cocontraction. The estimation error of the chosen model is acceptable (normalized root-mean-squared error: 0.15-0.29, R: 0.71-0.93) compared to previous studies (Doorenbosch and Harlaar, 2003; Doorenbosch and Harlaar, 2004; Doorenbosch, Joosten, and Harlaar, 2005), and this strategy provides a simple and effective solution for estimating knee joint moment from sEMG.

Real-time upper limb motion estimation from surface electromyography and joint angular velocities using an artificial neural network for human-machine cooperation.

A current challenge with human-machine cooperation systems is to estimate human motions to facilitate natural cooperation and safety of the human. It is a logical approach to estimate the motions from their sources (skeletal muscles); thus, we employed surface electromyography (SEMG) to estimate body motions. In this paper, we investigated a cooperative manipulation control by an upper limb motion estimation method using SEMG and joint angular velocities. The SEMG signals from five upper limb muscles and angular velocities of the limb joints were used to approximate the flexion-extension of the limb in the 2-D sagittal plane. The experimental results showed that the proposed estimation method provides acceptable performance of the motion estimation [normalized root mean square error (NRMSE) <0.15, correlation coefficient (CC) >0.9] under the noncontact condition. From the analysis of the results, we found the necessity of the angular velocity input and estimation error feedback due to physical contact. Our results suggest that the estimation method can be useful for a natural human-machine cooperation control.

Bimanual shoulder flexion system with surface electromyography for hemiplegic patients after stroke: A preliminary study.

A robot-assisted bimanual shoulder flexion rehabilitation system with surface electromyography (sEMG) for hemiplegic patients after stroke is presented as a preliminary study before clinical test. The assistive system driven by combination of bimanual mirror imaging motion and sEMG in order to induce continuous voluntary stimulation to muscle and nerve of the patients. In this paper, hardware design, controller with impedance compensation of actuator using disturbance observer (DOB) for back-drivable operation, and sEMG signal processing to obtain desired assistive torque are also reported. The performance of impedance compensation and assistive operation of the system with sEMG were verified by experiments with a healthy participant. This system is expected to help to recover functionality of neural/musculoskeletal system to hemiplegic patients.

Real-time pinch force estimation by surface electromyography using an artificial neural network.

The palmar pinch force estimation is highly relevant not only in biomechanical studies, the analysis of sports activities, and ergonomic design analyses but also in clinical applications such as rehabilitation, in which information about muscle forces influences the physician's decisions on diagnosis and treatment. Force transducers have been used for such purposes, but they are restricted to grasping points and inevitably interfere with the human haptic sense because fingers cannot directly touch the environmental surface. We propose an estimation method of the palmar pinch force using surface electromyography (SEMG). Three myoelectric sites on the skin were selected on the basis of anatomical considerations and a Fisher discriminant analysis (FDA), and SEMG at these sites yields suitable information for pinch force estimation. An artificial neural network (ANN) was implemented to map the SEMG to the force, and its structure was optimized to avoid both under- and over-fitting problems. The resulting network was tested using SEMG signals recorded from the selected myoelectric sites of ten subjects in real time. The training time for each subject was short (approximately 96s), and the estimation results were promising, with a normalized root mean squared error (NRMSE) of 0.081+/-0.023 and a correlation (CORR) of 0.968+/-0.017.