Search Results (14)

Epidermal sensors are pivotal components of next-generation wearable technologies. They offer transformative potential in health monitoring, motion tracking, and biomedical applications. This potential stems from their ultra-thin design, skin compatibility, and ability to continuously detect physiological signals. The long-term functionality relies on advanced power systems balancing flexibility, energy density, and environmental resilience. This review highlights four key power strategies: chemical batteries, biofuel cells, environmental energy harvesters, and wireless power transfer. Breakthroughs in multidimensional materials address challenges in ion transport, catalytic stability, and mechanical durability. Structural innovations mitigate issues like dendrite growth and enzyme degradation. These systems enable applications spanning biomarker analysis, motion sensing, and environmental monitoring. By integrating these advancements, this review concludes with a prospective outlook on future directions for epidermal sensor power systems. Full article

The development of a high-performance, low-cost, and simply fabricated flexible three-dimensional (3D) force sensor is essential for the future development of electronic skins suitable for the detection of normal and shear forces for several human motions. In this study, a sandwich-structured flexible 3D force tactile sensor based on a polyethylene-carbon composite material (velostat) is presented. The sensor has a large measuring range, namely, 0–12 N in the direction of the normal force and 0–2.6 N in the direction of the shear force. For normal forces, the sensitivity is 0.775 N⁻¹ at 0–1 N, 0.107 N⁻¹ between 1 and 3 N, and 0.003 N⁻¹ at 3 N and above. For shear forces, the measured sensitivity is 0.122 and 0.12 N⁻¹ in x- and y-directions, respectively. Additionally, the sensor exhibits good repeatability and stability after 2500 cycles of loading and releasing. The response and recovery times of the sensor are as fast as 40 and 80 ms, respectively. Furthermore, we prepared a glove-like sensor array. When grasping the object using the tactile glove, the information about the force applied to the sensing unit can be transmitted through a wireless system in real-time and displayed on a personal computer (PC). The prepared flexible 3D force sensor shows broad application prospects in the field of smart wearable devices. Full article

In the last 20 years, research into and clinical use of wireless ingestible capsules (WIC) has increased, with capsule endoscopy being the most common application in clinical practice. Additionally, there has been an increased research interest in sensing capsules. To maximize the usefulness of the information provided by these devices, it is crucial to know their location within the gastrointestinal tract. The main WIC localization methods in research include radio frequency approaches, video-based methods, and magnetic-based methods. Of these methods, the magnetic-based methods show the most potential in terms of localization accuracy. However, the need for an external transmitting (or sensing) array poses an important limitation, as evidenced by most of the reported methods involving a rigid structure. This poses a challenge to its wearability and performance in daily life environments. This paper provides an overview of the state of the art on magnetic-based localization for WIC, followed by a proof of concept of a system that aims to solve the wearability challenges. Comparative performance simulations of different transmitter arrays are presented. The effect of including one or two receiver coils in the WIC is also evaluated in the simulation. Experimental localization results for a planar transmitter array and for a more wearable belt-shaped transmitter are presented and compared. A localization mean absolute error (MAE) as low as 6.5 mm was achieved for the planar array in a volume of 15 cm × 15 cm × 15 cm, starting at a 5 cm distance from the transmitter. Evaluating the belt array in a similar volume of interest (15 cm × 15 cm × 15 cm starting at 7.5 cm distance from the transmitter) resulted in an MAE of 13.1 mm across the volume and a plane-specific MAE as low as 9.5 mm when evaluated at a 12.5 cm distance. These initial results demonstrate comparable performances between these two transmitters, while the belt array has the potential to enable measurements in daily-life environments. Despite these promising results, it was identified that an improvement in the model for the magnetic field when using transmitter coils with ferrite cores is necessary and is likely to result in better localization accuracy. This belt-array approach, together with compensation techniques for body motion, as recently reported for rigid arrays, has the potential to enable WIC localization in uncontrolled environments with minimal impact on the user’s daily life. Full article

Older adults are more vulnerable to falling due to normal changes due to aging, and their falls are a serious medical risk with high healthcare and societal costs. However, there is a lack of automatic fall detection systems for older adults. This paper reports (1) a wireless, flexible, skin-wearable electronic device for both accurate motion sensing and user comfort, and (2) a deep learning-based classification algorithm for reliable fall detection of older adults. The cost-effective skin-wearable motion monitoring device is designed and fabricated using thin copper films. It includes a six-axis motion sensor and is directly laminated on the skin without adhesives for the collection of accurate motion data. To study accurate fall detection using the proposed device, different deep learning models, body locations for the device placement, and input datasets are investigated using motion data based on various human activities. Our results indicate the optimal location to place the device is the chest, achieving accuracy of more than 98% for falls with motion data from older adults. Moreover, our results suggest a large motion dataset directly collected from older adults is essential to improve the accuracy of fall detection for the older adult population. Full article

Whole-body center of gravity (CG) movements in relation to the center of pressure (COP) offer insights into the balance control strategies of the human body. Existing CG measurement methods using expensive measurement equipment fixed in a laboratory environment are not intended for continuous monitoring. The development of wireless sensing technology makes it possible to expand the measurement in daily life. The insole system is a wearable device that can evaluate human balance ability by measuring pressure distribution on the ground. In this study, a novel protocol (data preparation and model training) for estimating the 3-axis CG trajectory from vertical plantar pressures was proposed and its performance was evaluated. Input and target data were obtained through gait experiments conducted on 15 adult and 15 elderly males using a self-made insole prototype and optical motion capture system. One gait cycle was divided into four semantic phases. Features specified for each phase were extracted and the CG trajectory was predicted using a bi-directional long short-term memory (Bi-LSTM) network. The performance of the proposed CG prediction model was evaluated by a comparative study with four prediction models having no gait phase segmentation. The CG trajectory calculated with the optoelectronic system was used as a golden standard. The relative root mean square error of the proposed model on the 3-axis of anterior/posterior, medial/lateral, and proximal/distal showed the best prediction performance, with 2.12%, 12.97%, and 12.47%. Biomechanical analysis of two healthy male groups was conducted. A statistically significant difference between CG trajectories of the two groups was shown in the proposed model. Large CG sway of the medial/lateral axis trajectory and CG fall of the proximal/distal axis trajectory is shown in the old group. The protocol proposed in this study is a basic step to have gait analysis in daily life. It is expected to be utilized as a key element for clinical applications. Full article

Wearable integrated systems that rely on liquid metal commonly require an extremely complicated, high-cost fabrication process, while lacking multiple sensing functions without conductive wires connected to external electronic systems. A multi-sensing wearable patch independent from sophisticated manufacturing method and excessive use of wires has yet to be developed. Herein, we introduce a wireless, battery-free, and skin-attachable patch with multiple sensing capacities, utilizing a low-budget, less time-consuming and design-customizable fabrication method. In an effort to achieve our goal, the general sensing system architecture is promoted, which consists of a semi-liquid alloy Ni-GaIn based strain sensor and a co-designed near-field-communication (NFC) tag integrating thermistor, photoresistor, as well as sensor interface circuits, enabling energy-autonomous power supply and wireless data transmission. In human volunteers, the patch was mounted on the skin surface to demonstrate real-time temperature and light intensity signal monitoring. Further evaluation of body motion capturing involved finger bending and swallowing, demonstrating the feasibility of practical applications in different scenarios. Continuous and simultaneous multi-type signal sensing using the wearable patch should enrich the dimensions of measurements of body response to daily activities, unveiling the potential for remote human health monitoring, advanced human–machine interfaces, and other applications of interest. Full article

Reliable, easy-to-use, and cost-effective wearable sensors are desirable for continuous measurements of flexions and torsions of the trunk, in order to assess risks and prevent injuries related to body movements in various contexts. Piezo-capacitive stretch sensors, made of dielectric elastomer membranes coated with compliant electrodes, have recently been described as a wearable, lightweight and low-cost technology to monitor body kinematics. An increase of their capacitance upon stretching can be used to sense angular movements. Here, we report on a wearable wireless system that, using two sensing stripes arranged on shoulder straps, can detect flexions and torsions of the trunk, following a simple and fast calibration with a conventional tri-axial gyroscope on board. The piezo-capacitive sensors avoid the errors that would be introduced by continuous sensing with a gyroscope, due to its typical drift. Relative to stereophotogrammetry (non-wearable standard system for motion capture), pure flexions and pure torsions could be detected by the piezo-capacitive sensors with a root mean square error of ~8° and ~12°, respectively, whilst for flexion and torsion components in compound movements, the error was ~13° and ~15°, respectively. Full article

Continuous monitoring of physical motion, which can be successfully achieved via a wireless flexible wearable electronic device, is essential for people to ensure the appropriate level of exercise. Currently, most of the flexible LC pressure sensors have low sensitivity because of the high Young’s modulus of the dielectric properties (such as PDMS) and the inflexible polymer films (as the substrate of the sensors), which don’t have excellent stretchability to conform to arbitrarily curved and moving surfaces such as joints. In the LC sensing system, the metal rings, as the traditional readout device, are difficult to meet the needs of the portable readout device for the integrated and planar readout antenna. In order to improve the pressure sensitivity of the sensor, the Ecoflex microcolumn used as the dielectric of the capacitive pressure sensor was prepared by using a metal mold copying method. The Ecoflex elastomer substrates enhanced the levels of conformability, which offered improved capabilities to establish intimate contact with the curved and moving surfaces of the skin. The pressure was applied to the sensor by weights, and the resonance frequency curves of the sensor under different pressures were obtained by the readout device connected to the vector network analyzer. The experimental results show that resonant frequency decreases linearly with the increase of applied pressure in a range of 0–23,760 Pa with a high sensitivity of −2.2 MHz/KPa. We designed a coplanar waveguide-fed monopole antenna used to read the information of the LC sensor, which has the potential to be integrated with RF signal processing circuits as a portable readout device and a higher vertical readout distance (up to 4 cm) than the copper ring. The flexible LC pressure sensor can be attached to the skin conformally and is sensitive to limb bending and facial muscle movements. Therefore, it has the potential to be integrated as a body sensor network that can be used to monitor physical motion. Full article

Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn. Advances in miniaturized sensor and materials research produces patchable inertial measurement units (IMUs). In this paper, a hand gesture recognition system using a single patchable six-axis IMU attached at the wrist via recurrent neural networks (RNN) is presented. The IMU comprises IC-based electronic components on a stretchable, adhesive substrate with serpentine-structured interconnections. The proposed patchable IMU with soft form-factors can be worn in close contact with the human body, comfortably adapting to skin deformations. Thus, signal distortion (i.e., motion artifacts) produced for vibration during the motion is minimized. Also, our patchable IMU has a wireless communication (i.e., Bluetooth) module to continuously send the sensed signals to any processing device. Our hand gesture recognition system was evaluated, attaching the proposed patchable six-axis IMU on the right wrist of five people to recognize three hand gestures using two models based on recurrent neural nets. The RNN-based models are trained and validated using a public database. The preliminary results show that our proposed patchable IMU have potential to continuously monitor people’s motions in remote settings for applications in mobile health, human–computer interaction, and control gestures recognition. Full article

Harvesting biomechanical energy is a viable solution to sustainably powering wearable electronics for continuous health monitoring, remote sensing, and motion tracking. A hybrid insole energy harvester (HIEH), capable of harvesting energy from low-frequency walking step motion, to supply power to wearable sensors, has been reported in this paper. The multimodal and multi-degrees-of-freedom low frequency walking energy harvester has a lightweight of 33.2 g and occupies a small volume of 44.1 cm³. Experimentally, the HIEH exhibits six resonant frequencies, corresponding to the resonances of the intermediate square spiral planar spring at 9.7, 41 Hz, 50 Hz, and 55 Hz, the Polyvinylidene fluoride (PVDF) beam-I at 16.5 Hz and PVDF beam-II at 25 Hz. The upper and lower electromagnetic (EM) generators are capable of delivering peak powers of 58 µW and 51 µW under 0.6 g, by EM induction at 9.7 Hz, across optimum load resistances of 13.5 Ω and 16.5 Ω, respectively. Moreover, PVDF-I and PVDF-II generate root mean square (RMS) voltages of 3.34 V and 3.83 V across 9 MΩ load resistance, under 0.6 g base acceleration. As compared to individual harvesting units, the hybrid harvester performed much better, generated about 7 V open-circuit voltage and charged a 100 µF capacitor up to 2.9 V using a hand movement for about eight minutes, which is 30% more voltage than the standalone piezoelectric unit in the same amount of time. The designed HIEH can be a potential mobile source to sustainably power wearable electronics and wireless body sensors. Full article

Wearable indoor localization can now find applications in a wide spectrum of fields, including the care of children and the elderly, sports motion analysis, rehabilitation medicine, robotics navigation, etc. Conventional inertial measurement unit (IMU)-based position estimation and radio signal indoor localization methods based on WiFi, Bluetooth, ultra-wide band (UWB), and radio frequency identification (RFID) all have their limitations regarding cost, accuracy, or usability, and a combination of the techniques has been considered a promising way to improve the accuracy. This investigation aims to provide a cost-effective wearable sensing solution with data fusion algorithms for indoor localization and real-time motion analysis. The main contributions of this investigation are: (1) the design of a wireless, battery-powered, and light-weight wearable sensing device integrating a low-cost UWB module-DWM1000 and micro-electromechanical system (MEMS) IMU-MPU9250 for synchronized measurement; (2) the implementation of a Mahony complementary filter for noise cancellation and attitude calculation, and quaternions for frame rotation to obtain the continuous attitude for displacement estimation; (3) the development of a data fusion model integrating the IMU and UWB data to enhance the measurement accuracy using Kalman-filter-based time-domain iterative compensations; and (4) evaluation of the developed sensor module by comparing it with UWB- and IMU-only solutions. The test results demonstrate that the average error of the integrated module reached 7.58 cm for an arbitrary walking path, which outperformed the IMU- and UWB-only localization solutions. The module could recognize lateral roll rotations during normal walking, which could be potentially used for abnormal gait recognition. Full article

With the rapid development of low-power consumption wireless sensors and wearable electronics, harvesting energy from human motion to enable self-powered sensing is becoming desirable. Herein, a pair of smart insoles integrated with piezoelectric poly(vinylidene fluoride) (PVDF) nanogenerators (NGs) are fabricated to simultaneously harvest energy from human motion and monitor human gait signals. Multi-target magnetron sputtering technology is applied to form the aluminum electrode layers on the surface of the PVDF film and the self-powered insoles are fabricated through advanced 3D seamless flat-bed knitting technology. Output responses of the NGs are measured at different motion speeds and a maximum value of 41 V is obtained, corresponding to an output power of 168.1 μW. By connecting one NG with an external circuit, the influence of external resistance, capacitor, and motion speed on the charging characteristics of the system is systematically investigated. To demonstrate the potential of the smart insoles for monitoring human gait signals, two subjects were asked to walk on a treadmill at different speeds or with a limp. The results show that one can clearly distinguish walking with a limp from regular slow, normal, and fast walking states by using multiscale entropy analysis of the stride intervals. Full article

The standard technology used to capture motion for biomechanical analysis in sports has employed marker-based optical systems. While these systems are excellent at providing positional information, they suffer from a limited ability to accurately provide fundamental quantities such as velocity and acceleration (hence forces and torques) during high-speed motion typical of many sports. Conventional optical systems require considerable setup time, can exhibit sensitivity to extraneous light, and generally sample too slowly to accurately capture extreme bursts of athletic activity. In recent years, wireless wearable sensors have begun to penetrate devices used in sports performance assessment, offering potential solutions to these limitations. This article, after determining pressing problems in sports that such sensors could solve and surveying the state-of-the-art in wearable motion capture for sports, presents a wearable dual-range inertial and magnetic sensor platform that we developed to enable an end-to-end investigation of high-level, very wide dynamic-range biomechanical parameters. We tested our system on collegiate and elite baseball pitchers, and have derived and measured metrics to glean insight into performance-relevant motion. As this was, we believe, the first ultra-wide-range wireless multipoint and multimodal inertial and magnetic sensor array to be used on elite baseball pitchers, we trace its development, present some of our results, and discuss limitations in accuracy from factors such as soft-tissue artifacts encountered with extreme motion. In addition, we discuss new metric opportunities brought by our systems that may be relevant for the assessment of micro-trauma in baseball. Full article

Recent advances in wearable sensor technologies for motion capture have produced devices, mainly based on magneto and inertial measurement units (M-IMU), that are now suitable for out-of-the-lab use with children. In fact, the reduced size, weight and the wireless connectivity meet the requirement of minimum obtrusivity and give scientists the possibility to analyze children’s motion in daily life contexts. Typical use of magneto and inertial measurement units (M-IMU) motion capture systems is based on attaching a sensing unit to each body segment of interest. The correct use of this setup requires a specific calibration methodology that allows mapping measurements from the sensors’ frames of reference into useful kinematic information in the human limbs’ frames of reference. The present work addresses this specific issue, presenting a calibration protocol to capture the kinematics of the upper limbs and thorax in typically developing (TD) children. The proposed method allows the construction, on each body segment, of a meaningful system of coordinates that are representative of real physiological motions and that are referred to as functional frames (FFs). We will also present a novel cost function for the Levenberg–Marquardt algorithm, to retrieve the rotation matrices between each sensor frame (SF) and the corresponding FF. Reported results on a group of 40 children suggest that the method is repeatable and reliable, opening the way to the extensive use of this technology for out-of-the-lab motion capture in children. Full article