Gait monitoring using hip joint angles offers a promising approach for person identification, leveraging the capabilities of smartphone inertial measurement units (IMUs). This study investigates the use of smartphone IMUs to extract hip joint angles for distinguishing individuals based on their gait patterns. The data were collected from 10 healthy subjects (8 males, 2 females) walking on a treadmill at 4 km/h for 10 min. A sensor fusion technique that combined accelerometer, gyroscope, and magnetometer data was used to derive meaningful hip joint angles. We employed various machine learning algorithms within the WEKA environment to classify subjects based on their hip joint pattern and achieved a classification accuracy of 88.9%. Our findings demonstrate the feasibility of using hip joint angles for person identification, providing a baseline for future research in gait analysis for biometric applications. This work underscores the potential of smartphone-based gait analysis in personal identification systems.

The demand for remote rehabilitation is increasing, opening up convenient and effective home-based therapy for the sick and elderly. In this study, we use AnyBody simulations to analyze muscle activity and determine key parameters for designing a rehabilitation exoskeleton, as well as selecting the appropriate motor torque to assist patients during rehabilitation sessions. The exoskeleton was designed with a PID control mechanism for the precise management of motor positions and joint torques, and it operates in both automated and teleoperation modes. Hip and knee movements are monitored via smartphone-based IMU sensors, enabling real-time feedback. Bluetooth communication ensures seamless control during various training scenarios. Our study demonstrates that remotely controlled rehabilitation systems can be implemented effectively, offering vital support not only during global health crises such as pandemics but also in improving the accessibility of rehabilitation services in remote or underserved areas. This approach has the potential to transform the way physical therapy can be delivered, making it more accessible and adaptable to the needs of a larger patient population.

Gait disorders, muscle weakness, spinal cord injuries (SCIs) and other work-related disorders have increased the need for rehabilitation exoskeletons—specifically, for the hip because a huge percentage of mechanical power comes from the hip joint. However, realising a lightweight rehabilitation hip exoskeleton for mobility and at-home use with reliable control is challenging. The devices developed are restricted by a joint actuator and energy source design and tend to have various uncertainties. Thus, this study tested the robustness of four optimal controller cases in a simulation-based environment. We sought to determine whether the most robust optimal controller consumed less energy and demonstrated better performance in tracking the desired signal. The robustness of the optimal cases was tested with the hip torque signals of healthy subjects. The number of sit-to-stand (STS) instances and the walking distance at various speeds were calculated. The results showed that the most robust case controller was more energy efficient for STS, but not for walking activity. Furthermore, this study provides compelling evidence that various optimal controllers have different degrees of robustness and effects on energy consumption.

Coronavirus caused pandemics as many viruses did through human history. The current pandemic causes overwhelmed healthcare system, locked down cities, and massive fatality among humans. Thus, different robots have been used since the COVID outbreak worldwide to reduce spreading infectious diseases and support frontline healthcare workers. This paper sets out the different robots implemented for hospital, non-hospital use, and possible use that can be deployed amidst the pandemic. A literature survey of versatile robots during COVID-19 is introduced. Roboticists contributed with wheeled and drone robots with various applications to assist medical care systems and society during the ongoing crisis. Pandemics are common throughout human history and difficult to avoid or prevent; thus, we intend to encourage societies, academia, engineers and innovators to invest more in robots that cannot catch the virus and consequently introduce beneficial solutions to fight such pandemic in the future.