Commonly, quantitative gait analysis post-stroke is performed in fully equipped laboratories housing costly technologies for quantitative evaluation of a patient’s movement capacity. Combining such technologies with an electromyography (EMG)-driven musculoskeletal model can estimate muscle force properties non-invasively, offering clinicians insights into motor impairment mechanisms. However, lab-constrained areas and time-demanding sensor setup and data processing limit the practicality of these technologies in routine clinical care. We presented wearable technology featuring a multi-channel EMG-sensorized garment and an automated muscle localization technique. This allows unsupervised computation of muscle-specific activations, combined with five inertial measurement units (IMUs) for assessing joint kinematics and kinetics during various walking speeds. Finally, the wearable system was combined with a person-specific EMG-driven musculoskeletal model (referred to as human digital twins), enabling the quantitative assessment of movement capacity at a muscle-tendon level. This human digital twin facilitates the estimation of ankle dorsi-plantar flexion torque resulting from individual muscle-tendon forces. Results demonstrate the wearable technology’s capability to extract joint kinematics and kinetics. When combined with EMG signals to drive a musculoskeletal model, it yields reasonable estimates of ankle dorsi-plantar flexion torques (R2 = 0.65 ± 0.21) across different walking speeds for post-stroke individuals. Notably, EMG signals revealing an individual’s control strategy compensate for inaccuracies in IMU-derived kinetics and kinematics when input into a musculoskeletal model. Our proposed wearable technology holds promise for estimating muscle kinetics and resulting joint torque in time-limited and space-constrained environments. It represents a crucial step toward translating human movement biomechanics outside of controlled lab environments for effective motor impairment monitoring.

Linkage fabrics are gaining in popularity and finding applications in architecture, aerospace, healthcare, and fashion because they can deliver materials with bespoke flexibility and strength through the geometric design of linkage nodes. In this article, we provide a perspective on linkage fabrics as a new class of programmable materials. We describe the theory and design principles of these linkage fabrics and show how they can be designed and simulated using digital tools, and fabricated using 3D printing. This digital approach overcomes a major obstacle to the adoption of these materials, namely their complexity. We show how simulation methods can be verified and calibrated through experimental testing. This perspective article also discusses design-led research challenges for linkage fabrics such as the development of wearable assistive devices for those with physical disabilities.

The Internet of Things (IoT) and wearable computing are crucial elements of modern information systems and applications in which advanced features for user interactivity and monitoring are required. However, in the fields of pervasive gaming, IoT has had limited real-world applications. In this work, we present a prototype of a wearable platform for pervasive games that combines IoT with wearable computing to enable the real-time monitoring of physical activity. The main objective of the solution is to promote the utilization of gamification techniques to enhance the physical activity of users through challenges and quests. This aims to create a symbolic link between the virtual gameplay and the real-world environment without the requirement of a smartphone. With the integration of sensors and wearable devices by design, the platform has the capability of real-time monitoring the users’ physical activity during the game. The system performance results highlight the efficiency and attractiveness of the wearable platform for gamifying physical activity.

Wearable activity trackers have emerged as valuable tools for health research, providing high-resolution data on measures such as physical activity. While most research on these devices has been conducted in high-income countries, there is growing interest in their use in the global south. This perspective discusses the challenges faced and strategies employed when using wearable activity trackers to test the effects of a school-based intervention for depression and anxiety among Kenyan youth. Lessons learned include the importance of validating data output, establishing an internal procedure for international procurement, providing on-site support for participants, designating a full-time team member for wearable activity tracker operation, and issuing a paper-based information sheet to participants. The insights shared in this perspective serve as guidance for researchers undertaking studies with wearables in similar settings, contributing to the evidence base for mental health interventions targeting youth in the global south. Despite the challenges to set up, deploy and extract data from wearable activity trackers, we believe that wearables are a relatively economical approach to provide insight into the daily lives of research participants, and recommend their use to other researchers.

The science and technology of wearable robots are steadily advancing, and the use of such robots in our everyday life appears to be within reach. Nevertheless, widespread adoption of wearable robots should not be taken for granted, especially since many recent attempts to bring them to real-life applications resulted in mixed outcomes. The aim of this article is to address the current challenges that are limiting the application and wider adoption of wearable robots that are typically worn over the human body. We categorized the challenges into mechanical layout, actuation, sensing, body interface, control, human–robot interfacing and coadaptation, and benchmarking. For each category, we discuss specific challenges and the rationale for why solving them is important, followed by an overview of relevant recent works. We conclude with an opinion that summarizes possible solutions that could contribute to the wider adoption of wearable robots.

This review meta-analysis combines and compares the findings of previously published works in the field of soft wearable robots (SWRs) that provide active methods of actuation for assistive and augmentative purposes. A thorough investigation of major contributions in the field of an SWR is made to analyze trends in the field focused on fluidic and cable-driven systems, prevalent and successful approaches, and identify the future direction of SWRs and active actuation strategies. Types of soft actuators used in wearables are outlined, as well as general practices for fabrication methods of soft actuators and considerations for human–robot interface designs of garment-like exosuits. An overview of well-known and emerging upper body (UB)- and lower body (LB)-assistive technologies is categorized by the specific joints and degree of freedom (DoF) assisted and which actuator methodology is provided. Different use cases for SWRs are addressed, as well as implementation strategies and design applications.

In this paper, a simple and efficient method to increase the gain and bandwidth of the wearable antennas used in several medical/communications systems is presented. To increase the gain and bandwidth simultaneously, the triple transmission lines (TTLs) method has been used. With this method, the frequency ranges of 1.7–2.5 and 5.4–5.95 GHz are covered with dual-band responses. Also, the simulated maximum gain at 2 and 5.8 GHz is equal to 8.26 and 9.86 dB, respectively. Using the TTLs method, the second frequency band (5.4–5.95 GHz) is achieved. Also, the gain improvement in operating frequencies is more than 4 dB compared to the conventional antenna. The dimensions of the proposed wearable high-gain antenna are 80 × 92 × 2 mm3 or 0.57 × 0.67 × 0.01 λg3 at 2 GHz. Finally, a dual-band sample antenna for use in medical systems was fabricated with a flexible felt substrate and its characteristics were measured. There is a good fit between the measurement and simulation results.

A compact multiple input multiple output (MIMO) antenna operating at 2.45 GHz industrial scientific and medical band is presented for wearable devices. Open-end slotting is used to miniaturize the antenna dimensions. Inverted U-shaped ground stub is incorporated to reduce mutual coupling. On-body performance is analyzed on a three-layered equivalent tissue phantom model. The wide bandwidth of 300 MHz and port isolation of 30 dB are obtained from measured results. The antenna shows the efficiency of 40% and directivity of 4.56 dBi when placed at a gap of “s” = 4 mm from the body. Broadside radiation pattern and low specific absorption rate make the antenna suitable for on-body communication. Further, diversity performance is measured in terms of envelope correlation coefficient (ECC), diversity gain (DG), and channel capacity loss (CCL). The value of ECC is 0.025, DG is 9.98 dB, and CCL is 0.12 bits/s/Hz at 2.45 GHz. Antenna robustness is examined by bending the structure at different radii along the x-axis and y-axis. Performance of the proposed structure is reliable with structural deformation.

This paper reports an integration of dual band microstrip antenna with thin film amorphous silicon solar cell which creates a wearable system to harvest microwave energy. The multiple layers in the encapsulation of the thin film solar cell are used as a substrate for microstrip antenna. The rectifier and matching circuit are designed on cotton jeans material and the whole system is mechanically supported by the foam of 5 mm thick. The performance of the antenna is studied for the mechanical bending condition. The device has maintained good power conversion efficiency. The efficiency of the voltage doubler is tested by varying radio frequency power levels from −30 to10 dBm. The voltage doubler conversion efficiency at 1.85 and 2.45 GHz are 58 and 43%, respectively, for a load of 7.5 kΩ for an input power level of −5 dBm.