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Falling is one of the most common causes of hip fracture and death in older adults. A comparison of the biomechanics of the gait in fallers and non-fallers older adults, especially joint coordination and coordination variability, enables the understanding of mechanisms that underpin falling. Therefore, we compared lower-extremity intra-joint coordination and its variability between fallers and non-fallers older adults during gait. A total of 26 older adults, comprising 13 fallers, took part in this study. The participants walked barefoot at a self-selected speed on a 10-m walkway. Gait kinematics in the dominant leg during 10 cycles were captured with 10 motion tracking cameras at a sampling rate of 100 Hz. Spatiotemporal gait parameters, namely, cadence, walking speed, double support time, stride time, width, and length, as well as intra-joint coordination and coordination variability in the sagittal plane were compared between the two groups. Results showed that fallers walked with significant lower cadence, walking speed, and stride length but greater double support and stride time than non-fallers. Significant differences in the ankle-to-knee, knee-to-hip, and ankle-to-hip coordination patterns between fallers and non-fallers and less coordination variability in fallers compared to non-fallers in some instants of the gait cycles were observed. The differences in spatiotemporal gait parameters in fallers compared to non-fallers may indicate an adaptation resulting from decreased efficiency to decrease the risk of falling. Moreover, the differences in segment coordination and its variability may indicate an inconsistency in neuromuscular control. It may also indicate reduced ability to control the motion of the leg in preparation for foot contact with the ground and the knee and ankle motions during loading response. Finally, such differences may show less control in generating power during the push-off phase in fallers. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study is to examine the lower extremity intra-segment coordination and variability of road cyclists during pedaling at different intensities. Methods: Eleven semi-professional road cyclists perform four trials at workloads of 50%, 75%, 100%, and 125% of their maximum power output in a randomized order. Thigh, shank, and foot range of motions (ROM) and the coordination and variability of these segments are compared across different pedaling intensities. Results: Foot ROM in the sagittal plane and shank ROM in the transverse plane are significantly different between different pedaling intensities. Moreover, specific coupling patterns and variabilities are observed across the pedaling cycle; however, they were not significantly different across different pedaling intensities in four pedaling phases. Conclusion: The results highlight the role of knee extensors and plantar flexors during the first and second half of the propulsion phase of pedaling, respectively. Thigh abduction dominancy with faster movement compared to the shank indicates a more valgus stress during the propulsive phase of pedaling, which can increase the risk of overuse injuries in the knee. Moreover, the smaller variability during the transition between the propulsive and recovery phases indicates a reduction in degrees of freedom and may increase the risk of overuse injuries. [ABSTRACT FROM AUTHOR]

The aim of the present study was to predict the kinematics of the knee and the ankle joints during a squat training task of different intensities. Lower limb surface electromyographic (sEMG) signals and the 3-D kinematics of lower extremity joints were recorded from 19 body builders during squat training at four loading conditions. A long-short term memory (LSTM) was used to estimate the kinematics of the knee and the ankle joints. The accuracy, in terms root-mean-square error (RMSE) metric, of the LSTM network for the knee and ankle joints were 6.774 ± 1.197 and 6.961 ± 1.200, respectively. The LSTM network with inputs processed by cross-correlation (CC) method showed 3.8% and 4.7% better performance in the knee and ankle joints, respectively, compared to when the CC method was not used. Our results showed that in the prediction, regardless of the intensity of movement and inter-subject variability, an off-the-shelf LSTM decoder outperforms conventional fully connected neural networks. [ABSTRACT FROM AUTHOR]

Humans typically fixate on objects before moving their arm to grasp the object. Patients with ALS disorder can also select the object with their intact eye movement, but are unable to move their limb due to the loss of voluntary muscle control. Though several research works have already achieved success in generating the correct grasp type from their brain measurement, we are still searching for fine controll over an object with a grasp assistive device (orthosis/exoskeleton/robotic arm). Object orientation and object width are two important parameters for controlling the wrist angle and the grasp aperture of the assistive device to replicate a human-like stable grasp. Vision systems are already evolved to measure the geometrical attributes of the object to control the grasp with a prosthetic hand. However, most of the existing vision systems are integrated with electromyography and require some amount of voluntary muscle movement to control the vision system. Due to that reason, those systems are not beneficial for the users with brain-controlled assistive devices. Here, we implemented a vision system which can be controlled through the human gaze. We measured the vertical and horizontal electrooculogram signals and controlled the pan and tilt of a cap-mounted webcam to keep the object of interest in focus and at the centre of the picture. A simple 'signature' extraction procedure was also utilized to reduce the algorithmic complexity and system storage capacity. The developed device has been tested with ten healthy participants. We approximated the object orientation and the size of the object and determined an appropriate wrist orientation angle and the grasp aperture size within 22 ms. The combined accuracy exceeded 75%. The integration of the proposed system with the brain-controlled grasp assistive device and increasing the number of grasps can offer more natural manoeuvring in grasp for ALS patients. [ABSTRACT FROM AUTHOR]

Understanding how upper-limb prostheses are used in daily life helps to improve the design and robustness of prosthesis control algorithms and prosthetic components. However, only a very small fraction of published research includes prosthesis use in community settings. The cost, limited battery life, and poor generalisation may be the main reasons limiting the implementation of home-based applications. In this work, we introduce the design of a cost-effective Arduino-based myoelectric control system with wearable electromyogram (EMG) sensors. The design considerations focused on home studies, so the robustness, user-friendly control adjustments, and user supports were the main concerns. Three control algorithms, namely, direct control, abstract control, and linear discriminant analysis (LDA) classification, were implemented in the system. In this paper, we will share our design principles and report the robustness of the system in continuous operation in the laboratory. In addition, we will show a first real-time implementation of the abstract decoder for prosthesis control with an able-bodied participant. [ABSTRACT FROM AUTHOR]