2005년 대한 생화학·분자생물학회 하계학술대회를 다녀와서

Resistance change under mechanical stimuli arouses mass operational heat, damaging the performance, lifetime, and reliability of stretchable electronic devices, therefore rapid thermal heat dissipating is necessary. Here we report a stretchable strain sensor with outstanding thermal management. Besides a high stretchability and sensitivity testified by human motion monitoring, as well as long-term durability, an enhanced thermal conductivity from the casted thermoplastic polyurethane-boron nitride nanosheets layer helps rapid heat transmission to the environments, while the porous electrospun fibrous thermoplastic polyurethane membrane leads to thermal insulation. A 32% drop of the real time saturated temperature is achieved. For the first time we in-situ investigated the dynamic operational temperature fluctuation of stretchable electronics under repeating stretching-releasing processes. Finally, cytotoxicity test confirms that the nanofillers are tightly restricted in the nanocomposites, making it harmless to human health. All the results prove it an excellent candidate for the next-generation of wearable devices. Though stretchable strain sensors are attractive for next-generation applications due to their high sensitivity, heat generated in these devices limits their reliability. Here, the authors report boron nitride nanosheet-based stretchable strain sensors with enhanced thermal management.

/pdf/a-high-performance-wearable-strain-sensor-with-advanced-hcckhsuu0z.pdf

A high performance wearable strain sensor with advanced thermal management for motion monitoring.

Hydrogels offer tissue-like compliance, stretchability, fracture toughness, ionic conductivity and compatibility with biological tissues. However, their electrical conductivity ( 350 S cm−1) and is capable of delivering direct current while maintaining soft compliance (Young’s modulus < 10 kPa) and deformability. Micrometre-sized silver flakes are suspended in a polyacrylamide–alginate hydrogel matrix and, after going through a partial dehydration process, the flakes form percolating networks that are electrically conductive and robust to mechanical deformations. To illustrate the capabilities of our silver–hydrogel composite, we use the material in a stingray-inspired swimmer and a neuromuscular electrical stimulation electrode. A hydrogel composite that consists of micrometre-sized silver flakes suspended in a polyacrylamide–alginate hydrogel matrix exhibits a high electrical conductivity of over 350 S cm−1 and a low Young’s modulus of less than 10 kPa.

An electrically conductive silver–polyacrylamide–alginate hydrogel composite for soft electronics

金光雄 著, 「관료와 발전」(서울 : 평민사, 1986)

Equalization for digitd conimunicatiou~ constitutes a very particular blind deconvoliition problem in that the received signal is cyclostationary. Oversampling (OS) (w.r.t. the symbol rate) of the cyclostationary received signal leads to a stationary vect.or-valued signal (polyphase representation (PR)). OS also leads to a fractionally-spa.ced channel model and equalizer. In the F'R, channel and equalizer can be considered as an analysis and synthesis filter hank. Zero-forcing p equalization corresponds to a perfect-reconstruction Iter bank. We show that in the OS (:aye FIR ZF equalizers exist for a FIR channel. In the PR, the multichannel linear prediction of the noiseless received signal becomes singular eventually, reminiscenc of the singlechannel prediction of a sum of sinusoids. A:. a result, the chaiinel can be identified from the received signal second-order statistics by linear prediction in the noise-free case, and by rising the Pisarenko method when there is a,dditive noise. In the given data case, Music (subspace) or MI. te(hniqiies can be applied.

http://ieeexplore.ieee.org/iel2/3104/8836/00389749.pdf

Blind fractionally-spaced equalization, perfect-reconstruction filter banks and multichannel linear prediction

This paper asks: “Can we push the prevailing range limits of commercial passive RFIDs?”. Today’s commercial passive RFIDs report ranges of 5-15 meters at best. This constrains RFIDs to be detected only at specific checkpoints in warehouses, stores and factories today, leaving them outside of communication range beyond these spaces. State-of-the-art approaches to improve the range of RFIDs develop new tag hardware that necessarily sacrifices some of the most attractive features of passive RFIDs such as their low cost, small form-factor or the absence of a battery. We present PushID, a system that exploits collaboration between readers to enhance the range of commercial passive RFID tags, without altering the tags whatsoever. PushID uses distributed MIMO to coherently combine signals across geographically separated RFID readers at the tags. In doing so, it resolves the chicken-or-egg problem of inferring the optimal beamforming parameters to beam energy to a tag without any feedback from the tag itself, which needs this energy to respond in the first place. A prototype evaluation of PushID with 8 distributed RFID readers reveals a range of 64-meters to the closest reader and a 7.4×, 1.2× and 1.6× improvement in range compared to state-of-the-art commercial readers and other two schemes [10, 33].

/pdf/pushing-the-range-limits-of-commercial-passive-rfids-48jycmsivi.pdf

Pushing the Range Limits of Commercial Passive RFIDs

This paper presents WiSh, a solution that makes ordinary surfaces shape-aware, relaying their real-time geometry directly to a user's handheld device. WiSh achieves this using inexpensive, light-weight and battery-free RFID tags attached to these surfaces tracked from a compact single-antenna RFID reader. In doing so, WiSh enables several novel applications: shape-aware clothing that can detect a user's posture, interactive shape-aware toys or even shape-aware bridges that report their structural health. WiSh's core algorithm infers the shape of ordinary surfaces using the wireless channels of signals reflected off RFID tags received at a single-antenna RFID reader. Indeed, locating every RFID tag using a single channel measurement per-tag is challenging, given that neither their 3-D coordinates nor orientation are known a priori. WiSh presents a novel algorithm that models the geometric constraints between the coordinates of the RFID tags based on flexibility of the surface upon which they are mounted. By inferring surface curvature parameters rather than the locations of individual RFID tags, we greatly reduce the number of variables our system needs to compute. Further, WiSh overcomes a variety of system-level challenges stemming from signal multipath, stretching of fabric and modeling large surfaces. We implement WiSh on commodity RFID readers and tags attached to a variety of surfaces and demonstrate mm-accurate shape-tracking across various applications.

WiSh: Towards a Wireless Shape-aware World using Passive RFIDs

RFID has been widely used for activity and gesture recognition in emerging interaction paradigms given its low cost, lightweight, and pervasiveness. However, current learning-based approaches on RFID sensing require significant efforts in data collection, feature extraction, and model training. To save data processing effort, we present MicroFluID, a novel RFID artifact based on a multiple-chip structure and microfluidic switches, which informs the input state by directly reading variable ID information instead of retrieving primitive signals. Fabricated on flexible substrates, four types of microfluidic switch circuits are designed to respond to external physical events, including pressure, bend, temperature, and gravity. By default, chips are disconnected into the circuit owing to the reserved gaps in transmission line. While external input or status change occurs, conductive liquid floating in the microfluidics channels will fill the gap(s), creating a connection to certain chip(s). In prototyping the device, we conducted a series of simulations and experiments to explore the feasibility of the multi-chip tag design, key fabrication parameters, interaction performance, and users' perceptions.

MicroFluID

Wireless sensing has demonstrated the potential of using Wi-Fi signals to track people and objects, even behind walls.Yet, prior work in this space aims to merely detect the presence of objects around corners, rather than their type. In this paper, we explore the feasibility of the following re-search question: ?Can commodity Wi-Fi radios detect both the location and type of moving objects around them?". We present IntuWition, a complementary sensing system that can sense the location and type of material of objects in the environment, including those out of line-of-sight. It achieves this by sensing wireless signals reflected off surrounding objects using commodity Wi-Fi radios, whose signals penetrate walls and occlusions. At the core of IntuWition is the idea that different materials reflect and scatter polarized waves in different ways. We build upon ideas from RADAR Polarimetry to detect the material of objects across spatial locations, despite mobility of the sensing device and the hardware non-idealities of commodity Wi-Fi radios. A detailed feasibility study reveals an average accuracy of 95% in line-of-sight and 92% in non-line-of-sight in classifying five types of materials:copper, aluminum, plywood, birch, and human. Finally, we present a proof-of-concept application of our system on an autonomous UAV that uses its onboard Wi-Fi radios to sense whether an occlusion is a person versus another UAV.

https://dl.acm.org/doi/pdf/10.1145/3300061.3345442

On the Feasibility of Wi-Fi Based Material Sensing

This paper presents an RF-based assistive technology for voice impairments (i.e., dysphonia), which occurs in an estimated 1% of the global population. We specifically focus on acquired voice disorders where users continue to be able to make facial and lip gestures associated with speech. Despite the rich literature on assistive technologies in this space, there remains a gap for a solution that neither requires external infrastructure in the environment, battery-powered sensors on skin or body-worn manual input devices. We present RFTattoo, which to our knowledge is the first wireless speech recognition system for voice impairments using batteryless and flexible RFID tattoos. We design specialized wafer-thin tattoos attached around the user's face and easily hidden by makeup. We build models that process signal variations from these tattoos to a portable RFID reader to recognize various facial gestures corresponding to distinct classes of sounds. We then develop natural language processing models that infer meaningful words and sentences based on the observed series of gestures. A detailed user study with 10 users reveals 86% accuracy in reconstructing the top-100 words in the English language, even without the users making any sounds.

https://dl.acm.org/doi/pdf/10.1145/3369812

Jingxian Wang

Papers

Pushing the Range Limits of Commercial Passive RFIDs

WiSh: Towards a Wireless Shape-aware World using Passive RFIDs

MicroFluID

On the Feasibility of Wi-Fi Based Material Sensing

RFID Tattoo: A Wireless Platform for Speech Recognition