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1. Fusion Learning on Multiple-Tag RFID Measurements for Respiratory Rate Monitoring

   https://doi.org/10.1109/BIBE50027.2020.00082  

   Hansen, Stephen ; Schwartz, Daniel ; Stover, Jesse ; Tajin, Md Abu ; Mongan, William M. ; Dandekar, Kapil R. ( October 2020 , 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE))

   null (Ed.)

   Future advances in the medical Internet of Things (IoT) will require sensors that are unobtrusive and passively powered. With the use of wireless, wearable, and passive knitted smart garment sensors, we monitor infant respiratory activity. We improve the utility of multi-tag Radio Frequency Identification (RFID) measurements via fusion learning across various features from multiple tags to determine the magnitude and temporal information of the artifacts. In this paper, we develop an algorithm that classifies and separates respiratory activity via a Regime Hidden Markov Model compounded with higher-order features of Minkowski and Mahalanobis distances. Our algorithm improves respiratory rate detection by increasing the Signal to Noise Ratio (SNR) on average from 17.12 dB to 34.74 dB. The effectiveness of our algorithm in increasing SNR shows that higher-order features can improve signal strength detection in RFID systems. Our algorithm can be extended to include more feature sources and can be used in a variety of machine learning algorithms for respiratory data classification, and other applications. Further work on the algorithm will include accurate parameterization of the algorithm's window size. 

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2. A Fully-Flexible Solution-Processed Autonomous Glucose Indicator

   https://doi.org/10.1038/s41598-019-43425-x  

   Yuen, Jonathan D. ; Baingane, Ankit ; Hasan, Qumrul ; Shriver-Lake, Lisa C. ; Walper, Scott A. ; Zabetakis, Daniel ; Breger, Joyce C. ; Stenger, David A. ; Slaughter, Gymama ( May 2019 , Scientific Reports)

   We present the first demonstration of a fully-flexible, self-powered glucose indicator system that synergizes two flexible electronic technologies: a flexible self-powering unit in the form of a biofuel cell, with a flexible electronic device - a circuit-board decal fabricated with biocompatible microbial nanocellulose. Our proof-of-concept device, comprising an enzymatic glucose fuel cell, glucose sensor and a LED indicator, does not require additional electronic equipment for detection or verification; and the entire structure collapses into a microns-thin, self-adhering, single-centimeter-square decal, weighing less than 40 mg. The flexible glucose indicator system continuously operates a light emitting diode (LED) through a capacitive charge/discharge cycle, which is directly correlated to the glucose concentration. Our indicator was shown to operate at high sensitivity within a linear glucose concentration range of 1 mM–45 mM glucose continuously, achieving a 1.8 VDC output from a flexible indicator system that deliver sufficient power to drive an LED circuit. Importantly, the results presented provide a basis upon which further development of indicator systems with biocompatible diffusing polymers to act as buffering diffusion barriers, thereby allowing them to be potentially useful for low-cost, direct-line-of-sight applications in medicine, husbandry, agriculture, and the food and beverage industries.

    

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3. Computational imaging without a computer: seeing through random diffusers at the speed of light

   https://doi.org/10.1186/s43593-022-00012-4  

   Luo, Yi ; Zhao, Yifan ; Li, Jingxi ; Çetintaş, Ege ; Rivenson, Yair ; Jarrahi, Mona ; Ozcan, Aydogan ( January 2022 , eLight)

   Imaging through diffusers presents a challenging problem with various digital image reconstruction solutions demonstrated to date using computers. Here, we present a computer-free, all-optical image reconstruction method to see through random diffusers at the speed of light. Using deep learning, a set of transmissive diffractive surfaces are trained to all-optically reconstruct images of arbitrary objects that are completely covered by unknown, random phase diffusers. After the training stage, which is a one-time effort, the resulting diffractive surfaces are fabricated and form a passive optical network that is physically positioned between the unknown object and the image plane to all-optically reconstruct the object pattern through an unknown, new phase diffuser. We experimentally demonstrated this concept using coherent THz illumination and all-optically reconstructed objects distorted by unknown, random diffusers, never used during training. Unlike digital methods, all-optical diffractive reconstructions do not require power except for the illumination light. This diffractive solution to see through diffusers can be extended to other wavelengths, and might fuel various applications in biomedical imaging, astronomy, atmospheric sciences, oceanography, security, robotics, autonomous vehicles, among many others.

    

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4. Through the Soil Long Range Wireless Power Transfer for Agricultural IoT Networks

   https://doi.org/10.1109/TIE.2023.3250743  

   Nieman, Brandon T. ; Johnson, Christopher S. ; Pearce, Matthew ; Marcrum, Tyler ; Thorne, M. Caleb ; Ashby, Carter ; Neste, C. W. ( April 2023 , IEEE Transactions on Industrial Electronics)

   Kuperman, Alon (Ed.)

   Increasing the spatial and temporal density of data using networked sensors, known as the Internet of Things (IoT), can lead to enhanced productivity and cost savings in a host of industries. Where applications involve large outdoor expanses, such as farming, oil and gas, or defense, large regions of unelectrified land could yield significant benefits if instrumented with a high density of IoT systems. The major limitation of expanding IoT networks in such applications stems from the challenge of delivering power to each sensing device. Batteries, generators, and renewable sources have predominately been used to address the challenge, but these solutions require constant maintenance or are sensitive to environmental factors. This work presents a novel approach where conduction currents through soil are utilized for the wireless powering of sensor networks, initial investigation is within an 0.8-ha (2-acre) area. The technique is not line-of-sight, powers all devices simultaneously through near-field mechanics, and has the ability to be minimally invasive to the working environment. A theory of operation is presented and the technique is experimentally demonstrated in an agricultural setting. Scaling and transfer parameters are discussed. 

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5. Synthetic Muscle Electroactive Polymer (EAP) pressure sensing and controlled shape-morphing for robotic grippers

   https://doi.org/10.1117/12.2583295  

   Briggs, Calum ; Cheng, Tianyu ; Meredith, Margot ; Vicars, Peter N. ; Rasmussen, Lenore ; Zhong, Alexander ( March 2021 , Proc. SPIE 11587, Electroactive Polymer Actuators and Devices (EAPAD) XXIII,)

   Madden, John D. ; Anderson, Iain A. ; Shea, Herbert R. (Ed.)

   Ras Labs makes Synthetic Muscle™, which is a class of electroactive polymer (EAP) based materials and actuators that sense pressure (gentle touch to high impact), controllably contract and expand at low voltage (1.5 V to 50 V, including use of batteries), and attenuate force. We are in the robotics era, but robots do have their challenges. Currently, robotic sensing is mainly visual, which is useful up until the point of contact. To understand how an object is being gripped, tactile feedback is needed. For handling fragile objects, if the grip is too tight, breakage occurs, and if the grip is too loose, the object will slip out of the grasp, also leading to breakage. Rigid robotic grippers using a visual feedback loop can struggle to determine the exact point and quality of contact. Robotic grippers can also get a stuttering effect in the visual feedback loop. By using soft Synthetic Muscle™ based EAP pads as the sensors, immediate feedback was generated at the first point of contact. Because these pads provided a soft, compliant interface, the first point of contact did not apply excessive force, allowing the force applied to the object to be controlled. The EAP sensor could also detect a change in pressure location on its surface, making it possible to detect and prevent slippage by then adjusting the grip strength. In other words, directional glide provided feedback for the presence of possible slippage to then be able to control a slightly tighter grip, without stutter, due to both the feedback and the soft gentleness of the fingertip-like EAP pads themselves. The soft nature of the EAP fingertip pad also naturally held the gripped object, improving the gripping quality over rigid grippers without an increase in applied force. Analogous to finger-like tactile touch, the EAPs with appropriate coatings and electronics were positioned as pressure sensors in the fingertip or end effector regions of robotic grippers. This development of using Synthetic Muscle™ based EAPs as soft sensors provided for sensors that feel like the pads of human fingertips. Basic pressure position and magnitude tests have been successful, with pressure sensitivity down to 0.05 N. Most automation and robots are very strong, very fast, and usually need to be partitioned away from humans for safety reasons. For many repetitive tasks that humans do with delicate or fragile objects, it would be beneficial to use robotics; whether it is for agriculture, medical surgery, therapeutic or personal care, or in extreme environments where humans cannot enter, including with contagions that have no cure. Synthetic Muscle™ was also retrofitted as actuator systems into off-the-shelf robotic grippers and is being considered in novel biomimetic gripper designs, operating at low voltages (less than 50 V). This offers biomimetic movement by contracting like human muscles, but also exceeds natural biological capabilities by expanding under reversed electric polarity. Human grasp is gentle yet firm, with tactile touch feedback. In conjunction with shape-morphing abilities, these EAPs also are being explored to intrinsically sense pressure due to the correlation between mechanical force applied to the EAP and its electronic signature. The robotic field is experiencing phenomenal growth in this fourth phase of the industrial revolution, the robotics era. The combination of Ras Labs’ EAP shape-morphing and sensing features promises the potential for robotic grippers with human hand-like control and tactile sensing. This work is expected to advance both robotics and prosthetics, particularly for collaborative robotics to allow humans and robots to intuitively work safely and effectively together. 

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