Elastomeric Electronic Skin for Prosthetic Tactile Sensation

This report demonstrates a wearable elastomer‐based electronic skin including resistive sensors for monitoring finger articulation and capacitive tactile pressure sensors that register distributed pressure along the entire length of the finger. Pressure sensitivity in the order of 0.001 to 0.01 kPa^?1 for pressures from 5 to 405 kPa, which includes much of the range of human physiological sensing, is achieved by implementing soft, compressible silicone foam as the dielectric and stretchable thin‐metal films. Integrating these sensors in a textile glove allows the decoupling of the strain and pressure cross‐sensitivity of the tactile sensors, enabling precise grasp analysis. The sensorized glove is implemented in a human‐in‐the‐loop system for controlling the grasp of objects, a critical step toward hand prosthesis with integrated sensing capabilities.     

Performance evaluation of sensing fabrics for monitoring physiological and biomechanical variables.

In the last few years, the smart textile area has become increasingly widespread, leading to developments in new wearable sensing systems. Truly wearable instrumented garments capable of recording behavioral and vital signals are crucial for several fields of application. Here we report on results of a careful characterization of the performance of innovative fabric sensors and electrodes able to acquire vital biomechanical and physiological signals, respectively. The sensing function of the fabric sensors relies upon newly developed strain sensors, based on rubber-carbon-coated threads, and mainly depends on the weaving topology, and the composition and deposition process of the conducting rubber-carbon mixture. Fabric sensors are used to acquire the respitrace (RT) and movement sensors (MS). Sensing features of electrodes, instead rely upon metal-based conductive threads, which are instrumental in detecting bioelectrical signals, such as electrocardiogram (ECG) and electromyogram (EMG). Fabric sensors have been tested during some specific tasks of breathing and movement activity, and results have been compared with the responses of a commercial piezoelectric sensor and an electrogoniometer, respectively. The performance of fabric electrodes has been investigated and compared with standard clinical electrodes.     

Sensing Glove for Brain Studies: Design and Assessment of Its Compatibility for fMRI With a Robust Test

In this paper, we describe a biomimetic-fabric-based sensing glove that can be used to monitor hand posture and gesture. Our device is made of a distributed sensor network of piezoresistive conductive elastomers integrated into an elastic fabric. This solution does not affect natural movement and hand gestures, and can be worn for a long time with no discomfort. The glove could be fruitfully employed in behavioral and functional studies with functional MRI (fMRI) during specific tactile or motor tasks. To assess MR compatibility of the system, a statistical test on phantoms is introduced. This test can also be used for testing the compatibility of mechatronic devices designed to produce different stimuli inside the MR environment. We propose a statistical test to evaluate changes in SNR and time-domain standard deviations between image sequences acquired under different experimental conditions. fMRI experiments on subjects wearing the glove are reported. The reproducibility of fMRI results obtained with and without the glove was estimated. A good similarity between the activated regions was found in the two conditions.     

A Liquid Metal Based Multimodal Sensor and Haptic Feedback Device for Thermal and Tactile Sensation Generation in Virtual Reality

Virtual reality (VR) has been widely used for training, gaming, and entertainment, and the value of VR is continually increasing as a contact-free technology. For an immersive VR experience, measuring finger movements and providing appropriate feedback to the hand are as important as visual information, given the necessity of the hands for activities in daily life. Thus, a hand-worn VR device with motion sensors and haptic feedback is desirable. In this paper, a multimodal sensing and feedback glove is developed with soft, stretchable, lightweight, and compact sensor and heater sheets manufactured by direct ink writing (DIW) of liquid metal, eutectic gallium-indium (eGaIn). In the sensor sheet, ten sensors and three vibrators are embedded to measure finger movements and provide vibro-haptic feedback. The other heater sheet provides thermo-haptic sensation in accurate and rapid manner via model-based feedback control even under stretched conditions. The multimodal sensing and feedback glove allows users to feel the contact status and discriminate materials with different temperature. Performance of the proposed multimodal glove is verified under VR environments including touching and pushing two blocks of different materials and grabbing a heated metal ball submerged in hot water.     

A wearable health care system based on knitted integrated sensors.

A comfortable health monitoring system named WEALTHY is presented. The system is based on a textile wearable interface implemented by integrating sensors, electrodes, and connections in fabric form, advanced signal processing techniques, and modern telecommunication systems. Sensors, electrodes and connections are realized with conductive and piezoresistive yarns. The sensorized knitted fabric is produced in a one step process. The purpose of this paper is to show the feasibility of a system based on fabric sensing elements. The capability of this system to acquire simultaneously several biomedical signals (i.e. electrocardiogram, respiration, activity) has been investigated and compared with a standard monitoring system. Furthermore, the paper presents two different methodologies for the acquisition of the respiratory signal with textile sensors. Results show that the information contained in the signals obtained by the integrated systems is comparable with that obtained by standard sensors. The proposed system is designed to monitor individuals affected by cardiovascular diseases, in particular during the rehabilitation phase. The system can also help professional workers who are subject to considerable physical and psychological stress and/or environmental and professional health risks.     

Photonic crystal fiber sensors for minimally invasive surgical devices

The measurement of interaction forces in minimally invasive surgical devices, sensorized with photonic crystal fiber (PCF) sensors, is presented in this paper. Two types of PCF sensors are used: a tapered PCF interferometer and a microhole-collapsed PCF interferometer for the detection of interaction forces generated in surgical devices without the influence of ambient temperature variation. The demonstration devices used for force characterization are a laparoscopic scissor and a standard surgical scissor blade. The force sensitivity of each sensorized blade is examined and compared with fiber Bragg grating (FBG)-sensorized blades. Results show that the PCF-sensorized surgical blades outperform the blades fitted with the FBG sensors during static load measurement.     

Wearable Stretchable Dry and Self-Adhesive Strain Sensors with Conformal Contact to Skin for High-Quality Motion Monitoring

Wearable stretchable strain sensors can have important applications in many areas. However, the high noise is a big hurdle for their application to monitor body movement. The noise is mainly due to the motion artifacts related to the poor contact between the sensors and skin. Here, wearable stretchable dry and self-adhesive strain sensors that can always form conformal contact to skin even during body movement are demonstrated. They are prepared via solution coating and consist of two layers, a dry adhesive layer made of biocompatible elastomeric waterborne polyurethane and a sensing layer made of a non-adhesive composite of reduced graphene oxide and carbon nanotubes. The adhesive layer makes the sensors conformal to skin, while the sensing layer exhibits a resistance sensitive to strain. The sensors are used to accurately monitor both small- and large-scale body movements, including various joint movements and muscle movements. They can always generate high-quality signals even on curvilinear skin surface and during irregular skin deformation. The sensitivity is remarkably higher while the noise is saliently lower than the non-adhesive strain sensors. They can also be used to monitor the movements along two perpendicular directions, which cannot be achieved by the non-adhesive strain sensors.     

Motion Capture of the Human Body Using Multiple Depth Sensors

The movements of the human body are difficult to capture owing to the complexity of the three‐dimensional skeleton model and occlusion problems. In this paper, we propose a motion capture system that tracks dynamic human motions in real time. Without using external markers, the proposed system adopts multiple depth sensors (Microsoft Kinect) to overcome the occlusion and body rotation problems. To combine the joint data retrieved from the multiple sensors, our calibration process samples a point cloud from depth images and unifies the coordinate systems in point clouds into a single coordinate system via the iterative closest point method. Using noisy skeletal data from sensors, a posture reconstruction method is introduced to estimate the optimal joint positions for consistent motion generation. Based on the high tracking accuracy of the proposed system, we demonstrate that our system is applicable to various motion‐based training programs in dance and Taekwondo.     

Rugged Textile Electrodes for Wearable Devices Obtained by Vapor Coating Off‐the‐Shelf,Plain‐Woven Fabrics

Fabrics are pliable, breathable, lightweight, ambient stable, and have unmatched haptic perception. Here, a vapor deposition method is used to transform off‐the‐shelf plain‐woven fabrics, such as linen, silk, and bast fiber fabrics, into metal‐free conducting electrodes. These fabric electrodes are resistant to wear, stable after laundering and ironing, and can be body‐mounted with little detriment to their performance. A unique by‐product of conformally vapor coating plain‐woven fabrics is that textile parameters, such as thread material and fabric porosity, significantly affect the conductivity of the resulting fabric electrodes. The resistivities of the electrodes reported herein are linearly, not exponentially, dependent on length, meaning that they can be feasibly incorporated into garments and other large‐area body‐mounted devices. Further, these fabric electrodes possess the feel, weight, breathability, and pliability of standard fabrics, which are important to enable adoption of wearable devices.     

基于ZigBee的穿戴式医疗监护系统节点的设计与实现

为了满足当今社会对穿戴式医疗监护的需求,设计并制作出了一种基于ZigBee技术的穿戴式医疗监护系统节点。该节点硬件部分采用了CC2530单片机和多种传感器,软件部分使用TI公司的Z-Stack协议栈,最终以相对低的成本实现了低生理、心理负荷下对人体体温、脉搏、生理姿态的获取。     

Robust planar textile antenna for wireless body LANs operating in 2.45 GHz ISM band

A single-feed rectangular-ring textile antenna is proposed for wireless body area networks operating in the 2.45 GHz ISM band. The conductive parts of the planar antenna consist of FlecTron/spl reg/, whereas fleece fabric is used as non-conductive antenna substrate. This results in a highly efficient, flexible and wearable antenna to be integrated in garments. The robustness of the antenna characteristics with respect to bending is proven.     

Nonwoven fabric active electrodes for biopotential measurement during normal daily activity

Body movement is responsible for most of the interference during physiological data acquisition during normal daily activities. In this paper, we introduce nonwoven fabric active electrodes that provide the comfort required for clothing while robustly recording physiological data in the presence of body movement. The nonwoven fabric active electrodes were designed and fabricated using both hand- and screen-printing thick-film techniques. Nonstretchable nonwoven (Evolon 100) was chosen as the flexible fabric substrate and a silver filled polymer ink (Creative Materials CMI 112-15) was used to form a transducer layer and conductive lines on the nonwoven fabrics. These nonwoven fabric active electrodes can be easily integrated into clothing for wearable health monitoring applications. Test results indicate that nonwoven textile-based sensors show considerable promise for physiological data acquisition in wearable healthcare monitoring applications.     

可穿戴式人体姿态识别系统研究进展

随着科技发展,基于可穿戴式传感器的研究逐渐得到重视,显现出功耗低、可携带性好、成本造价低、使用场景不受限制等独特优势。其中重要的一项应用是人体姿态识别,人体姿态识别过程主要分为人体运动信息采集、数据预处理、姿态角求解、模式识别特征的提取与识别。本文介绍了人体姿态识别技术的研究进程,总结了目前常用的传感器,最后对未来人体姿态识别技术发展进行展望。     

Deploying Wireless Sensor Networks under Limited Mobility Constraints

In this paper, we study the issue of sensor network deployment using limited mobility sensors. By limited mobility, we mean that the maximum distance that sensors are capable of moving to is limited. Given an initial deployment of limited mobility sensors in a field clustered into multiple regions, our deployment problem is to determine a movement plan for the sensors to minimize the variance in number of sensors among the regions and simultaneously minimize the sensor movements. Our methodology to solve this problem is to transfer the nonlinear variance/movement minimization problem into a linear optimization problem through appropriate weight assignments to regions. In this methodology, the regions are assigned weights corresponding to the number of sensors needed. During sensor movements across regions, larger weight regions are given higher priority compared to smaller weight regions, while simultaneously ensuring a minimum number of sensor movements. Following the above methodology, we propose a set of algorithms to our deployment problem. Our first algorithm is the optimal maximum flow-based (OMF) centralized algorithm. Here, the optimal movement plan for sensors is obtained based on determining the minimum cost maximum weighted flow to the regions in the network. We then propose the simple peak-pit-based distributed (SPP) algorithm that uses local requests and responses for sensor movements. Using extensive simulations, we demonstrate the effectiveness of our algorithms from the perspective of variance minimization, number of sensor movements, and messaging overhead under different initial deployment scenarios.     

基于MEMS的数据手套传感技术研究

目前主流的数据手套采用机械式、光纤式或者图像识别等方法来获取手势姿态,本文提出利用MEMS传感器（三轴陀螺、三轴加速度计和三轴磁阻）,根据惯性测量原理,采用基于四元数解算的扩展卡尔曼滤波信息融合方法来获得手指全姿态信息的方法。基于MEMS传感器设计的数据手套,穿戴方便,运动自由度大,抗干扰能力强,且不受光线条件的约束。测试和实验的结果表明,基于MEMS传感技术的数据手套稳定可靠,具有一定的创新性和实际应用参考价值。     

In virtual fashion

Computer graphics and virtual reality are being combined to enable clothes-shoppers to serve as their own clothes models for garments that are digitally fitted and converted into unique 2D patterns. Everything off the rack in effect becomes custom tailoring, choice of fabric and all. The author describes how the virtual reality mannequin is developed from digital images of the body. The virtual design studio is then described. The characteristics of the materials used are incorporated into garment design. The computer modeling of cloth drape is discussed     

Haptic Glove With MR Brakes for Virtual Reality

Haptic gloves open up the world of force feedback by allowing the user to pick up and feel virtual objects in a natural way. In most of the existing gloves, a remote box houses a large number of actuators and sensors. Power to the glove is transmitted via cables. If the haptic gloves were smaller, lighter, and easier to use and control, they could become more common as human-machine interfaces. Recent developments show that actuators based on active fluids, such as the magnetorheological (MR) fluids, can be viable alternatives in haptics. But these devices are desk- or floor-mounted and use relatively large MR brakes. In this research, we developed a compact MR brake that is about 25 mm in diameter, weighs 84 g, and can apply up to 899 Nmiddotmm torque. The compact size was achieved by stacking steel and aluminum rings to create a serpentine flux path through the fluid. Six brakes were used to build a force feedback glove called MR glove. The glove weighs 640 g and does not require any remote actuators. Results of usability experiments showed that the MR glove improved task completion times in grasping virtual objects and could convey stiffness information to the user.     

Highly Bendable and Rotational Textile Structure with Prestrained Conductive Sewing Pattern for Human Joint Monitoring

Human joints have respective ranges of motion and joint forces corresponding to each kind of joint; this necessitates considerations of the characteristics of human joints to fabricate wearable strain sensors conformable to the human body, and capable of precisely monitoring complex motions of the human body. In the present study, the “all textile‐based highly stretchable structure” that is capable of precisely sensing motions (folding and rotation) of the human joints (finger, wrist, elbow, spine, and knee) is fabricated by optimizing patterns (straight, blind, and zigzag) of conductive yarns employed as the conductive part of the strain sensor, and several textile substrates (braided elastic fabric, knit fabric, and woven fabric), having preferable elasticity and conformability employed for the fabrication of strain sensors suitable for human joints. In particular, the technology, enabling the prestraining of textile substrate, is exploited to fabricate a strain sensor that is capable of outputting selective signals corresponding to the folding motion of the spinal joint over a predetermined angle of motion, and the gait pattern of the wearer of the sensor, attached to his or her knee joint doing folding and rotational motions, is analyzed.     

Sensory feedback in a half-center oscillator model

We hypothesize that one role of sensorimotor feedback for rhythmic movements in biological organisms is to synchronize the frequency of movements to the mechanical resonance of the body. Our hypothesis is based on recent studies that have shown the advantage of moving at mechanical resonance and how such synchronization may be possible in biology. We test our hypothesis by developing a physical system that consists of a silicon-neuron central pattern generator (CPG), which controls the motion of a beam, and position sensors that provide feedback information to the CPG. The silicon neurons that we use are integrated circuits that generate neural signals based on the Hodgkin-Huxley dynamics. We use this physical system to develop a model of the interaction between the sensory feedback and the complex dynamics of the neurons to create the closed-loop system behavior. This model is then used to describe the conditions under which our hypothesis is valid and the general effects of sensorimotor feedback on the rhythmic movements of this system.     

基于多元数据融合的课堂表现智能检测系统设计

为了评估学生的上课行为,文章采用最新的头部姿态估计技术。此项技术能够捕捉当前人头部所做的各种动作与角度,例如低头、转头、仰头等。低头是大多数学生课堂上使用手机的惯用姿势,可以利用此项技术来监测其头部姿态从而进行评估。考虑到人脸检测的定位准确度问题,以及学生低头的动作不一定是使用手机,文章同时引入了无线信号侦测技术,捕获并检测当前教室里由于学生使用手机造成信号频繁收发的终端位置,与人脸检测的定位相结合,交叉定位,从而获得更精准的定位效果。