2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)最新文献_第10页

A 216 nW/channel DSP engine for triggering theta phase-locked brain stimulation 用于触发锁相脑刺激的216 nW/通道DSP引擎

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325189

Ahmed Alzuhair, D. Markovic

引用次数: 3

Spike context: A neuromorphic descriptor for pattern recognition 脉冲上下文:用于模式识别的神经形态描述符

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325188

Bharath Ramesh, Ngoc Anh Le Thi, G. Orchard, C. Xiang

引用次数: 5

Continuous active probing and modulation of neural networks with a wireless implantable system 用无线植入式系统连续主动探测和调制神经网络

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325195

V. Kremen, B. Brinkmann, Inyong Kim, Su-Youne Chang, J. Gompel, Jeffrey A. Herron, S. Baldassano, E. Patterson, B. Litt, T. Denison, G. Worrell

引用次数: 9

Inexpensive 1024-channel 3D telesonography system on FPGA 基于FPGA的廉价1024通道三维遥成像系统

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325108

A. Ibrahim, Damien Doy, Claudio Loureiro, Eliéva Pignat, F. Angiolini, M. Arditi, J. Thiran, G. Micheli

{"title":"Inexpensive 1024-channel 3D telesonography system on FPGA","authors":"A. Ibrahim, Damien Doy, Claudio Loureiro, Eliéva Pignat, F. Angiolini, M. Arditi, J. Thiran, G. Micheli","doi":"10.1109/BIOCAS.2017.8325108","DOIUrl":"https://doi.org/10.1109/BIOCAS.2017.8325108","url":null,"abstract":"Volumetrie ultrasound (US) is a very promising development of medical US imaging. An under-exploited advantage of volumetric US is the mitigation of the strict probe positioning constrains necessary to acquire 2D scans, potentially allowing the decoupling of US image acquisition and diagnosis. However, today's 3D US systems are large and beset by high power and cost requirements, making them only available in well-equipped hospitals. In this study, we propose the first telesonography-capable medical imaging system that supports up to 1024 channels, on par with the state of the art. As a first embodiment, we have implemented our design in a single development FPGA board of 26.7cm×14cm×0.16cm, with an estimated power consumption of 6.1 W. Moreover, we have equipped our platform with an automatic positioning module to help any operator defining the scan location, hence allowing for better remote diagnosis. Our design supports two types of data inputs: real-time via an optical connection and offline over Ethernet. The reconstructed images can be visualized on an HDMI screen. The estimated cost of the proposed prototype materials is less than 4000€.","PeriodicalId":361477,"journal":{"name":"2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114661748","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}

引用次数: 2

Electrode-shift tolerant myoelectric movement-pattern classification using extreme learning for adaptive sparse representations 基于极限学习的自适应稀疏表示的电极位移耐受肌电运动模式分类

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325201

Joseph L. Betthauser, Luke E. Osborn, R. Kaliki, N. Thakor

{"title":"Electrode-shift tolerant myoelectric movement-pattern classification using extreme learning for adaptive sparse representations","authors":"Joseph L. Betthauser, Luke E. Osborn, R. Kaliki, N. Thakor","doi":"10.1109/BIOCAS.2017.8325201","DOIUrl":"https://doi.org/10.1109/BIOCAS.2017.8325201","url":null,"abstract":"Myoelectric signal patterns can be used to predict the intended movements of amputees for prosthesis activation. Real-world prosthesis use introduces a variety of unpredictable conditional influences on these patterns, hindering the performance of classification algorithms and potentially leading to device abandonment. We have discovered a state-of-the-art classification method which is significantly more tolerant to these conditional influences. In our prior work, we presented a robust sparsity-based adaptive classification method that is tolerant to pattern deviations resulting from untrained limb positions and the prosthesis load. Herein, we demonstrate that this method is tolerant to the shifting or misalignment of the contact-electrode array which occurs during prosthesis use. We demonstrate the robustness of this approach in untrained electrode-site locations for amputee and able-bodied subjects, and report significant performance improvements over conventional myoelectric pattern recognition approaches. By showing that a single, unified method is robust across a variety of real-world condition spaces, clinicians are more likely to incorporate this method into myoelectric prosthesis controllers, resulting in improved utility and increased adoption among amputee users.","PeriodicalId":361477,"journal":{"name":"2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133584791","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}

引用次数: 3

A 71% efficient energy harvesting and power management unit for sub-μW power biomedical applications 用于亚μ w功率生物医学应用的71%效率的能量收集和电源管理单元

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325069

Abhishek Roy, B. Calhoun

引用次数: 7

Capacitively coupled ECG sensor system with digitally assisted noise cancellation for wearable application 电容耦合心电传感器系统与数字辅助降噪可穿戴应用

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325162

Yuki Nagasato, S. Izumi, H. Kawaguchi, M. Yoshimoto

{"title":"Capacitively coupled ECG sensor system with digitally assisted noise cancellation for wearable application","authors":"Yuki Nagasato, S. Izumi, H. Kawaguchi, M. Yoshimoto","doi":"10.1109/BIOCAS.2017.8325162","DOIUrl":"https://doi.org/10.1109/BIOCAS.2017.8325162","url":null,"abstract":"This paper describes a digitally assisted noise cancellation method for a capacitively coupled electrocardiogram (ECG) sensor. This sensor using an insulated electrode can measure ECG through an insulator such as clothing without direct skin contact. In wearable applications, this type of ECG sensor is superior in terms of usability compared with the pasted type ECG sensor. However, noise immunity is an important difficulty related to capacitively coupled ECG sensors because it requires very high input impedance and small input capacitance for the first-stage amplifier. This circuit characteristic considerably degrades its noise immunity for the power line noise and motion artifact. To address this difficulty, we propose the noise feedback method, which can improve the availability of a capacitively coupled ECG sensor. Noise caused by body movement and the surrounding environment included in the output of the AD converter is extracted by digital filters. DC offset, baseline fluctuation, and low-frequency component of body motion noise are extracted using a variable-gain loop filter. Power line noise is also extracted using a peak filter. Then the noise waveform is estimated from the result of the previous cycle. This noise information is DA converted and given feedback to the first stage amplifier. The proposed method was evaluated using prototype sensor in an actual environment. ECG measurements were confirmed in both two-electrode configuration and single-electrode configuration. Measurement results show that the power line noise can be suppressed to −29.2 dB at maximum.","PeriodicalId":361477,"journal":{"name":"2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116192245","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}

引用次数: 6

Non-contact biometric identification and authentication using microwave Doppler sensor 基于微波多普勒传感器的非接触式生物识别与认证

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325160

Takaaki Okano, S. Izumi, H. Kawaguchi, M. Yoshimoto

{"title":"Non-contact biometric identification and authentication using microwave Doppler sensor","authors":"Takaaki Okano, S. Izumi, H. Kawaguchi, M. Yoshimoto","doi":"10.1109/BIOCAS.2017.8325160","DOIUrl":"https://doi.org/10.1109/BIOCAS.2017.8325160","url":null,"abstract":"As described in this paper, we propose a non-contact biometrie authentication method with heartbeat features measured using a microwave Doppler sensor. The heartbeat component is measured as personal characteristic information attributable to individual differences in the myocardium and blood vessels. Biometric authentication using electrocardiogram (ECG) or pulse wave has been proposed in reports of earlier studies, but such methods require direct contact of the sensor with the human skin. However, heartbeat information can be measured and authenticated without contact to the skin when using the proposed method. The microwave Doppler sensor can detect minute vibrations of the body surface caused by heartbeat. The salient difficulty of the microwave Doppler sensor is noise contamination such as that caused by body motion. This study introduces the use of time-frequency analysis with an autoregressive model to reduce the noise influence and emphasize heartbeat features. An ID generation and authentication algorithm using a frequency feature of the heartbeat component is proposed. The proposed method was evaluated using measurements taken of 11 participants. Measurement results show a 92.8% true acceptance rate and a 3.9% equal error rate.","PeriodicalId":361477,"journal":{"name":"2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125152011","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}

引用次数: 9

Live demonstration: Programmable biphasic multi-channel constant current muscle stimulator with wireless power and data transfer 现场演示:具有无线供电和数据传输功能的可编程双相多通道恒流肌肉刺激器

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325095

Li Jing Ong, Marshal Dian Sheng Wong, Shih-Chiang Liu, Astrid Rusly, C. Tsai, Khay-Wai Leong, K. Ng, R. Jegadeesan, K. Voges, N. Thakor, S. Yen, S. Nag

引用次数: 1

Ultrawide range square wave impedance analysis circuit with ultra-slow ring-oscillator using gate-induced drain-leakage current 采用门感应漏漏电流的超慢环形振荡器超宽范围方波阻抗分析电路

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) Pub Date : 2017-10-01 DOI: 10.1109/BIOCAS.2017.8325165

Y. Takezawa, K. Kiyoyama, K. Shimokawa, Z. Qian, H. Kino, T. Fukushima, Tetsu Tanaka

引用次数: 1