The analysis of gait is a field of study whose popularity has grown due to its broad range of applications. Consequently, the development of tools for capturing gait has also seen a significant increase. This article presents the development of a system for gait analysis named STEPIO, which consists of four portable wireless modules, each equipped with a board comprised of a microcontroller and an inertial sensor. The system includes an intuitive graphical user interface that allows the acquisition, visualization, processing, and storage of the signals. The system offers a low-cost solution and the possibility of conducting studies in different environments and implementing innovative tools like the Internet of Things. To evaluate the performance of the system, 15 subjects without any diagnosed neuromusculoskeletal pathologies participated in the experimental protocol in which the range of motion of the knee and hip articulations was measured and compared with a reference optical system, resulting in a root mean square error of 2.7 degrees and a mean deviation of 2.44 degrees.

This paper describes the development of a portable system to measure surface electromyo-graphical (EMG) signals based on the Internet of Things. The system comprises eight modules designed to allow the wireless transmission of the surface EMG signals through a self-designed board to a graphical user interface (GUI). The GUI has three main stages: the configuration that enables the online adjustment of acquisition parameters; the acquisition stage for the visualization and storage of the data, as well as the upload or download to the cloud, contemplating encryption for data security, and finally, a rehabilitation video game that can be programmed according to the users’ needs. The system was tested on ten healthy participants, five men and five women, using a protocol for measuring signals during gait. The system showed a maximum data loss of $2.21 \%$ in a public network and $0.48 \%$ in a private network, a maximum stable frequency of 4700 Hz, and an autonomy of 128 minutes. Finally, it was compared with one commercial device and one clinical system.

This work describes the acquisition of kinematic and surface electromyography (sEMG) data from young and older adults during the execution of wrist movements using an upper limb rehabilitation robot (ULRR), along with a wristband equipped with inertial measurement units (IMUs) and sEMG sensors. These devices enable the observation of electrical muscle activation in the forearm during movement execution, providing valuable insights into the neuromuscular dynamics involved in motor control and movement mechanics. The description covers the robot configuration, sensor array, graphical user interfaces (GUIs) for visualizing robot data and biosignals, the experimental protocol, the database structure, and the signal processing and evaluation procedures. For the experimental protocol, 20 participants, 10 young and 10 older adults, were recruited. The test consisted of four basic wrist movements: radial deviation, ulnar deviation, flexion, and extension, which were performed in random order under the guidance of the ULRR GUI. The sEMG analysis indicated that older adults tend to overuse specific muscles and exhibit a higher percentage of compensatory movements $(38.5 \%)$ than younger participants $(24.25 \%)$. The study’s findings enable the identification of age-related differences in muscle activation and compensation, aiding the design of personalized rehabilitation programs and improved devices to enhance motor function in older adults.

Sitting, standing, and walking are fundamental activities crucial for maintaining independence in daily life. However, aging or lower limb injuries can impede these activities, posing obstacles to individuals' autonomy. In response to this challenge, we developed the LM-Ease (lower-limb movement ease), a compact and soft wearable robot designed to provide hip assistance. Its purpose is to aid users in carrying out essential daily activities such as sitting, standing, and walking. The LM-Ease features a fully actuated tendon-driven system that seamlessly transitions between assistance actuation profiles tailored for sitting, standing, and walking movements. This device provides the user with gravity support during stand-to-sit, and offers hip extension assistance pulling force during sit-to-stand and walking. Our preliminary results show that with the LM-Ease, healthy young adults (n$=$8) had significantly lower muscle activation: average reduction of 15.6% during stand-to-sit and 17.8% during sit-to-stand. Furthermore, with LM-Ease, participants demonstrated a 12.7% reduction in metabolic cost during ground walking. These evidences suggest that the LM-Ease holds potential in reducing muscular activation and energy expenditure during these fundamental daily activities. It could serve as a valuable tool for individuals seeking assistance in enhancing lower limb mobility, thereby bolstering their independence and overall quality of life.