{"title":"Continuous Blood Pressure Monitoring using Wrist-worn Bio-impedance Sensors with Wet Electrodes","authors":"Bassem Ibrahim, R. Jafari","doi":"10.1109/BIOCAS.2018.8584783","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584783","url":null,"abstract":"Continuous blood pressure (BP) monitoring is essential for diagnosis and management of cardiovascular disorders. Currently, BP is measured using cuff-based methods, which are obtrusive and not suitable for continuous monitoring. Estimation of BP using pulse transit time (PTT) is a prominent method that eliminates the need for a cuff. In this paper, we present a new method to estimate BP based on PTT measurements from an array of 2×2 bio-impedance sensors placed on the wrist, which can be integrated into a small wearable device such as a smart watch for continuous BP monitoring. Diastolic and systolic BP were estimated using AdaBoost regression model based on PTT features extracted from the wrist bio-impedance signals. Data was collected from three participants using our custom bio-impedance sensors. Our method can estimate BP accurately with correlation coefficient, mean absolute error (MAE) and standard deviation (STD) of 0.92, 1.71 and 2.46 mmHg for the diastolic BP and 0.94, 2.57 and 4.35 mmHg for the systolic BP.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"80 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125890058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Arimi, Y. Kimura, Toshiki Wakamori, Hiroo Yamamoto, S. Mizuno, T. Iwata, Kazuhiro Takahashi, K. Sawada
{"title":"High pH Resolution Extended Gate Type pH Image Sensors with the Charge Accumulation Circuit","authors":"Y. Arimi, Y. Kimura, Toshiki Wakamori, Hiroo Yamamoto, S. Mizuno, T. Iwata, Kazuhiro Takahashi, K. Sawada","doi":"10.1109/BIOCAS.2018.8584779","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584779","url":null,"abstract":"In order to observe the pH distribution of biological cells, we propose a pH image sensor with a new structure enabling high density and high sensitivity imaging. In the new proposed pH image sensor we add the charge accumulation circuit to the conventional 2-Tr pixel structure. In the charge accumulation operation, the circuit amplifies a signal by repeatedly transferring the signal charge from the pixel to the capacitor and thus it is expected that the pH resolution can be improved from the viewpoint of Signal-Noise Ratio (SNR). Since the charge accumulation circuit is designed with three transistors and one capacitor and is arranged outside the pixel array, a new pH image sensor is designed without large increase in area. Image sensors with charge accumulation circuits were designed and fabricated. We evaluate the fabricated pH image sensors, observe sensor gain increased by the charge accumulation circuit and realized the performance that enabled pH imaging. From the measurement result, the input-referred sensor noise is reduced by 82% compared with the conventional 2- Tr pixel structure sensor. Therefore, it is possible to realize pH resolution less than 0.02pH.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122277885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Injection-Locked Power Oscillator for Resonance Frequency Tracking in Wireless Power Transfer","authors":"Guangyin Feng, Ji-Jon Sit","doi":"10.1109/BIOCAS.2018.8584843","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584843","url":null,"abstract":"This paper presents a transmitter architecture for wireless power transfer with automatic resonance frequency tracking to maintain high efficiency over wide variations of antenna distance. By injection-locking the source oscillator to the output resonance in a positive feedback loop, the closed-loop transmitter functions as a power oscillator with the oscillation frequency determined by the most dominant resonance in the coupled antennas. We show that this frequency tracking minimizes the change in input impedance presented to the power amplifier (PA), and hence mitigates mismatch that can cause a sharp non-linear drop in PA efficiency. The power oscillator was tested well above and below critical coupling, and maintained PA efficiency above 60 % even when highly over-coupled at 25 % spacing (10mm/40mm) below critical coupling. Compared to an open-loop system, the charging range with efficiency over 50 % is doubled.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126259530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Avinash Sharma, Christopher L. Hunt, Asheesh Maheshwari, Luke E. Osborn, G. Levay, R. Kaliki, A. Soares, N. Thakor
{"title":"A Mixed-Reality Training Environment for Upper Limb Prosthesis Control","authors":"Avinash Sharma, Christopher L. Hunt, Asheesh Maheshwari, Luke E. Osborn, G. Levay, R. Kaliki, A. Soares, N. Thakor","doi":"10.1109/BIOCAS.2018.8584739","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584739","url":null,"abstract":"Adjusting to an amputation can often times be difficult for the body. Post-surgery, amputees not only have to incur expensive rehabilitation treatment costs, but also have to wait for up to several months before receiving a properly fitted prosthesis. We developed a mixed-reality training environment where amputees can train, at their own time and convenience, and interact with holographic objects, while also receiving tactile and proprioceptive feedback. We incorporate positional information through inertial sensors, touch and proprioception information through vibrational feedback, all integrated into an augmented-reality (AR) environment viewed through the Microsoft HoloLens TM. Training tasks were designed to account for limb rotation and object relocation in a three-dimensional space with a correct palm orientation essential for an intuitive grasp and release of objects. Our results showed an improved performance in training time, overshoot and completion rate with vibratory feedback (of both touch and proprioception) over without feedback. Furthermore, EMG activity was analyzed to estimate the muscular effort during each task.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122909301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Compact, Low-Noise, Chopped Front-End for Peripheral Nerve Recording in 180 nm CMOS","authors":"Jialin Liu, Ross M. Walker","doi":"10.1109/BIOCAS.2018.8584716","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584716","url":null,"abstract":"This manuscript presents a compact, low-noise signal conditioning chain for peripheral nerve recording from implanted microelectrodes. Chopping is used in combination with switched capacitor techniques to reduce circuit noise and area while achieving accurate passband gain and corner frequencies. Time-windowed-integration sampling is used to eliminate aliased noise introduced by the discrete time circuits and ripple introduced by chopping. Gain and transfer function accuracy are maintained while taking advantage of open loop structures. The circuit achieves an input-referred noise of 1.44 µVrmswhile implementing 58 dB gain across a bandwidth of 476 Hz to 9.75 kHz, draws 36.8 µA from a 1.8 V supply voltage corresponding to 3.45 NEF and 21 PEF, and achieves 0.034 mm2area per channel, which is 8x smaller than state-of-the-art peripheral nerve recording circuits with similar noise levels.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127820814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Live Demonstration: Miniaturized Compact NIRS probe based on SiPM and Pulsed VCSEL diode routes to wearable devices","authors":"Sreenil Saha, F. Lesage, M. Sawan","doi":"10.1109/BIOCAS.2018.8584748","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584748","url":null,"abstract":"Our goal is the development of a miniaturized Silicon Photomultiplier (SiPM) based compact probe for Near Infrared Spectroscopy (NIRS), that can be directly put in contact with the sample under test to obtain high diffused photon harvesting efficiency without the need for cumbersome optical fibers and lenses for light injection and collection. The proposed system is composed of two parts namely, i) pulsed light emission unit and ii) single-photon detection module. The size of the optical probe was reduced to 10mm by integrating multiple heterogenous chips from various foundry on a silicon interposer platform (‘2.5D’ stacking).","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121307309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mingzhu Long, Zehua Lan, Xiang Xie, Guolin Li, Zhihua Wang
{"title":"Image Enhancement Method Based on Adaptive Fraction Gamma Transformation and Color Restoration for Wireless Capsule Endoscopy","authors":"Mingzhu Long, Zehua Lan, Xiang Xie, Guolin Li, Zhihua Wang","doi":"10.1109/BIOCAS.2018.8584793","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584793","url":null,"abstract":"Wireless capsule endoscopy (WCE) plays an important role in gastrointestinal (GI) tract observation and disease diagnosis. However, due to the limited illumination and complex environment in GI tract, endoscopic images are usually not clear enough to be interpreted by doctors or used for further processing. Although many algorithms have been proposed to improve image quality from different aspects, the balance of algorithm complexity and image quality is still a challenge worth exploring. In this paper, we propose a novel function named adaptive fraction gamma transformation (AFGT) to enhance the quality of images captured by the WCE. Characteristics of AFGT are adaptive to different luminance in an image and self-tunable to the statistical characteristics of different images. Besides, HSI color space is adopted for color restoration, namely, the saturation component is linearly scaled according to the enhanced intensity component. Experimental results show that performances of the proposed method in both visual quality and objective assessments are better than that of the state-of-art methods.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116012166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zabir Ahmed, Jay W. Reddy, K. Deshpande, Ashwati Krishnan, Praveen Venkatesh, S. Kelly, P. Grover, M. Chamanzar
{"title":"Flexible Ultra-resolution Subdermal EEG Probes","authors":"Zabir Ahmed, Jay W. Reddy, K. Deshpande, Ashwati Krishnan, Praveen Venkatesh, S. Kelly, P. Grover, M. Chamanzar","doi":"10.1109/BIOCAS.2018.8584672","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584672","url":null,"abstract":"Scalp Electroencephalogram (EEG) is a popular, noninvasive method to record neural activity, commonly used in the clinical setting as a gold-standard for diagnosing many disorders, including epilepsy. The spatial resolution of scalp EEG is of critical concern for targeting surgical interventions and resultant patient outcomes. However, high-resolution spatial information is filtered and obscured by noise as electrical signals propagate through layers of tissue. We present a novel paradigm of high-density subdermal EEG arrays, capable of being implanted under the scalp to increase spatial resolution of EEG recordings while minimizing invasiveness compared to traditional implantable recording electrode arrays such as electrocorticography (ECoG) surface grids. In addition, our device can be chronically implanted, as opposed to traditional scalp EEG electrodes that need to be removed periodically for re-application of conductive electrode gel. We demonstrate the design, fabrication and electrical characterization of high-density subdermal EEG arrays realized in Parylene C polymer platform using an optimized microfabrication process. Devices are realized in a range of electrode diameters (200 microns – 1000 microns) and pitch (1 mm – 3.5 mm), to study the effects of electrode size and spacing on the spatial frequency content and redundancy of recorded neural signals. Electrochemical Impedance Spectroscopy (EIS) measurements, show an impedance of <10 kΩ (for 600 micron diameter) at 1 kHz. These high-density subdermal EEG probes will be used to validate our theoretical models of sampling and reconstructing neural activity from electric potentials.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115801216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A CMOS Perimeter Gated SPAD Based Digital Silicon Photomultiplier with Asynchronous AER Readout for PET Applications","authors":"Mst Shamim Ara Shawkat, N. Mcfarlane","doi":"10.1109/BIOCAS.2018.8584722","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584722","url":null,"abstract":"We present an architecture for a CMOS digital silicon photomultiplier (SiPM) based on an array of perimeter gated single photon avalanche diodes (PGSPADs). The designed digital SiPM is implemented in a standard 0.5 μm 2-poly, 3-metal CMOS process. In addition to preventing premature edge breakdown, PGSPADs have the capability to tune the noise floor, sensitivity, and dynamic range of the device. Each pixel includes data compression schemes and a single analog counter with a compact implementation to improve fill factor (FF). We implement a fully digital asynchronous address event representation (AER) readout. Simulation results show more than a factor of 10 temporal compression with an improvement of 25% in dead time at the microcell level of the pixel. The PGSPAD digital SiPM is designed for PET applications with an array-level dynamic range of 156 dB, and simulated worst case event readout speed of 20 MHz.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127402384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Minimum Precision Requirements for Deep Learning with Biomedical Datasets","authors":"Charbel Sakr, Naresh R Shanbhag","doi":"10.1109/BIOCAS.2018.8584732","DOIUrl":"https://doi.org/10.1109/BIOCAS.2018.8584732","url":null,"abstract":"Deep neural networks (DNNs) are powerful machine learning models but are typically deployed in large computing clusters due to their high computational and parameter complexity. Many biomedical applications require embedded inference on resource-constrained platforms thus causing a challenge when considering the deployment of DNNs. One method to address this challenge is via reduced precision implementations. We use an analytical method to determine suitable minimum precision requirements of DNNs and show its application to the CHB-MIT EEG seizure detection dataset and the Bonn dataset for brain electrical activity recognition. We show that our method leads to 2 × reduction in average precision and 45% complexity reduction compared to the minimum uniform precision assignment. Compared to a conventional 16-b precision assignment, our method leads to 9 x complexity reduction. Furthermore, we study the impact of network topology on precision and accuracy. Once again we find our method to be ~2× more efficient that the uniform assignment for all topologies considered.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127559317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}