Estimation of Lower Extremity Muscle Activity in Gait Using the Wearable Inertial Measurement Units and Neural Network.

The inertial measurement unit (IMU) has become more prevalent in gait analysis. However, it can only measure the kinematics of the body segment it is attached to. Muscle behaviour is an important part of gait analysis and provides a more comprehensive overview of gait quality. Muscle behaviour can be estimated using musculoskeletal modelling or measured using an electromyogram (EMG). However, both methods can be tasking and resource intensive. A combination of IMU and neural networks (NN) has the potential to overcome this limitation. Therefore, this study proposes using NN and IMU data to estimate nine lower extremity muscle activities. Two NN were developed and investigated, namely feedforward neural network (FNN) and long short-term memory neural network (LSTM). The results show that, although both networks were able to predict muscle activities well, LSTM outperformed the conventional FNN. This study confirms the feasibility of estimating muscle activity using IMU data and NN. It also indicates the possibility of this method enabling the gait analysis to be performed outside the laboratory environment with a limited number of devices.

Postural Control and Adaptation Strategy of Young Adults on Unstable Surface.

Balance control is essential for postural adjustment in physical activities. This study investigates the behavior of human postural control and the coordination and adaptation strategy of hip, knee, and ankle when standing on an unstable surface. Twenty participants were recruited. Four different conditions were investigated: a quiet bipedal stance with eyes open and eyes closed, and standing on an unstable surface with eyes open and eyes closed. Other than the joint angle, the standard body sway measures, such as sway area and sway velocity, were computed. A nonlinear time series measure, that is, sample entropy, was used to determine the regularity of the time series and body adaptability to change and perturbation. The results show that the body sway increases as the difficulty increases. This study also confirms the coordination of the hip, knee, and ankle to maintain body balance on the unstable surface by decreasing the joint angle and adopting a lower posture. Even though the individual joint has lower sample entropy value and is deemed to be rigid and less adaptive to perturbation, the postural control exhibits higher sample entropy value, particularly in the anterior-posterior direction, and has the ability to stabilize the body by manipulating the joints simultaneously. These outcomes suggest that an unstable surface not only challenges the human postural control, but also reduces the hip, knee, and ankle adaptability to perturbation, thus making it a great tool to train body balance.

Musculoskeletal Gait Simulation to Investigate Biomechanical Effect of Knee Brace.

Musculoskeletal modeling and simulation have been an emerging trend in human gait analysis. It allows the user to isolate certain biomechanical conditions and elucidate the dynamics of joints and muscles. This study used an open-source musculoskeletal modeling and simulation tool, opensim to investigate the biomechanical effect of knee brace. It collected gait data from thirty-eight participants and examined the gait spatio-temporal parameters, joint angles, and joint moments. Static optimization was performed to estimate the lower extremity muscle force. Statistical analysis was conducted to identify the difference between normal and braced gaits. The results demonstrated the feasibility of this method to investigate the interaction and coordination of lower extremity joints and muscles. The knee brace constrained the range of the motion of the knee during walking. It also changed the walking speed, step length, and stance-to-swing ratio. Several significant differences were found in the joint moments and muscle forces of the rectus femoris, gastrocnemius, soleus and tibialis anterior. Musculoskeletal modeling and simulation tool offers a less invasive and practical alternative to analyze human motion. It also provides a means to investigate the effect of medical devices such as knee brace, which can be potentially beneficial for the future design and development of such devices and for the derivation of future rehabilitation treatment to improve patient's gait.

Gamification and Control of Nitinol Based Ankle Rehabilitation Robot.

Conventional ankle rehabilitation exercises can be monotonous and repetitive. The use of robots and games can complement the existing practices, provide an engaging environment for the patient and alleviate the physiotherapist's workload. This paper presents an ankle rehabilitation robot that uses two nitinol wire actuators and a Pong game to provide foot plantarflexion and dorsiflexion exercises. Nitinol is a type of smart material that has high volumetric mechanical energy density and can produce translational motion. A two-state discrete antagonistic control is proposed to manipulate the actuators. The system was tested on healthy participants and stroke patients. The results showed that the robot was safe and compliant. The robot did not forcefully plantarflex or dorsiflex the foot when the participant exerted opposing force. The actuators worked antagonistically to flex to the foot as intended, in sync with the up and down motions of the player's bat in the game. These behaviors demonstrated the feasibility of a nitinol-based ankle rehabilitation robot and a simple and yet intuitive game in providing interactive rehabilitation exercise. The robot is expected to enhance the patient's experience, participation and compliance to the rehabilitation routine and to quantitatively monitor the patient's recovery progress.

The effect of asymmetrical gait induced by unilateral knee brace on the knee flexor and extensor muscles.

Asymmetrical stiff knee gait is a mechanical pathology that can disrupt lower extremity muscle coordination. A better understanding of this condition can help identify potential complications. This study proposes the use of dynamic musculoskeletal modelling simulation to investigate the effect of induced mechanical perturbation on the kneeand to examine the muscle behaviour without invasive technique. Thirty-eight healthy participants were recruited. Asymmetrical gait was simulated using knee brace. Knee joint angle, joint moment and knee flexor and extensor muscle forces were computed using OpenSim. Differences inmuscle force between normal and abnormal conditions were investigated using ANOVA and Tukey-Kramer multiple comparison test.The results revealed that braced knee experienced limited range of motion with smaller flexion moment occuring at late swing phase. Significant differences were found in all flexormuscle forces and in several extensor muscle forces (p<0.05). Normal knee produced larger flexor muscle force than braced knee. Braced knee generated the largest extensor muscle force at early swing phase. In summary, musculoskeletal modelling simulation can be a computational tool to map and detect the differences between normal and asymmetrical gaits.

Estimation of vertical ground reaction force during running using neural network model and uniaxial accelerometer.

Wearable technology has been viewed as one of the plausible alternatives to capture human motion in an unconstrained environment, especially during running. However, existing methods require kinematic and kinetic measurements of human body segments and can be complicated. This paper investigates the use of neural network model (NN) and accelerometer to estimate vertical ground reaction force (VGRF). An experimental study was conducted to collect sufficient samples for training, validation and testing. The estimated results were compared with VGRF measured using an instrumented treadmill. The estimates yielded an average root mean square error of less than 0.017 of the body weight (BW) and a cross-correlation coefficient greater than 0.99. The results also demonstrated that NN could estimate impact force and active force with average errors ranging between 0.10 and 0.18 of BW at different running speeds. Using NN and uniaxial accelerometer can (1) simplify the estimation of VGRF, (2) reduce the computational requirement and (3) reduce the necessity of multiple wearable sensors to obtain relevant parameters.

Moving toward Soft Robotics: A Decade Review of the Design of Hand Exoskeletons.

Soft robotics is a branch of robotics that deals with mechatronics and electromechanical systems primarily made of soft materials. This paper presents a summary of a chronicle study of various soft robotic hand exoskeletons, with different electroencephalography (EEG)- and electromyography (EMG)-based instrumentations and controls, for rehabilitation and assistance in activities of daily living. A total of 45 soft robotic hand exoskeletons are reviewed. The study follows two methodological frameworks: a systematic review and a chronological review of the exoskeletons. The first approach summarizes the designs of different soft robotic hand exoskeletons based on their mechanical, electrical and functional attributes, including the degree of freedom, number of fingers, force transmission, actuation mode and control strategy. The second approach discusses the technological trend of soft robotic hand exoskeletons in the past decade. The timeline analysis demonstrates the transformation of the exoskeletons from rigid ferrous materials to soft elastomeric materials. It uncovers recent research, development and integration of their mechanical and electrical components. It also approximates the future of the soft robotic hand exoskeletons and some of their crucial design attributes.

Developing interactive and simple electromyogram PONG game for foot dorsiflexion and plantarflexion rehabilitation exercise.

Gaming systems have been proven to be able to improve physical and cognitive skills. Several studies have integrated games to be part of rehabilitation program to improve functional ability of human limbs in performing activities of daily living. This paper presents the development of an interactive electromyogram (EMG) based PONG game for foot dorsifexion and plantarflexion exercise. PONG game is selected because it is a classical game that can be easily comprehended and can be played by young and old people. Two surface EMG sensors were used in this work to acquire muscle activity of tibialis anterior muscle and gastrocnemius muscle. An experimental study was carried out to examine the viability of this sensor as input to play the game. The results were satisfactory. This study further strengthens the viability of using muscle activity as an input for gaming system and as a mean to monitor patient rehabilitation progress.