{"title":"A robotic biarticulate leg model","authors":"M. A. Lewis, T. Klein","doi":"10.1109/BIOCAS.2008.4696873","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696873","url":null,"abstract":"Biarticulate muscles have been shown to perform the function of power transfer from the upper to lower leg, such as in tasks such as running, jumping, and stair climbing. A new robotic model of the human leg is described. This robotic leg transfers power from motors on the hip to the ankle. The importance of timing in maximizing the force transfer to push off at the toe is explored.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132335319","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":"An interference-resilient body channel transceiver for wearable body sensor network","authors":"Namjun Cho, Joonsung Bae, H. Yoo","doi":"10.1109/BIOCAS.2008.4696907","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696907","url":null,"abstract":"This work deals with a reliability issue of the body channel communication which uses the human body as a signal transmission medium. Due to the body antenna effect, lots of electromagnetic signals are coupled to the on-body receiver, degrading the SIR significantly. In order to reject the in-band interferences, an adaptive frequency hopping scheme using variable sub-channels is proposed. The use of dual frequency synthesizers for frequency hopping improves the data throughput and the acquisition time of the transceiver by eliminating the blank time overhead. The AFH transceiver realized with 0.18 mum CMOS process sustains 1.25 Mb/s throughput when the 10 interferences causing -25 dB SIR exist.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128594319","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":"Chemical bionics - a novel design approach using Ion Sensitive Field Effect Transistors","authors":"P. Georgiou, C. Toumazou","doi":"10.1109/BIOCAS.2008.4696916","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696916","url":null,"abstract":"This paper introduces Chemical Bionics in which the biochemical physiology of cells in the body are implemented in VLSI to make novel bio-inspired therapeutic devices. As an example, the glucose dependant electrophysiology of the pancreatic beta cell is implemented in silicon to form a novel bio-inspired prosthetic for glucose homeostasis of Type I diabetes. For this, the Ion Sensitive Field Effect Transistor (ISFET) is shown as a suitable chemical sensing front end, which allows CMOS monolithic implementation, as well as low power weak-inversion operation.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128659036","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":"Spectral analysis of sustained pupil light response to short and long wavelength light","authors":"W. Nowak, M. Nakayama, H. Ishikawa, K. Asakawa","doi":"10.1109/BIOCAS.2008.4696860","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696860","url":null,"abstract":"The purpose of this study was to assess the characteristics of frequency domain analysis of the sustained phase of pupil light reflex (PLR) to short and long wavelength light. In the work to be presented, spectra of the sustained phase of the PLR to short- and long- wavelength light in low and high photopic conditions were tested. The findings show that the proposed analysis method is valid and reveals significant differences between the analyzed cases. The findings suggest that the technique can provide useful information about the sustained phase of PLR which is always observed during PLR response to long light stimuli. Moreover, the proposed analysis method can be considered as a new, additional approach for testing the intrinsically photo-sensitive retinal ganglion cell activity mechanism.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115146424","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}
J. Holleman, D. Yeager, R. Prasad, Joshua R. Smith, B. Otis
{"title":"NeuralWISP: An energy-harvesting wireless neural interface with 1-m range","authors":"J. Holleman, D. Yeager, R. Prasad, Joshua R. Smith, B. Otis","doi":"10.1109/BIOCAS.2008.4696868","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696868","url":null,"abstract":"We present the NeuralWISP, a wireless neural interface operating from harvested RF energy. The NeuralWISP is compatible with commercial RFID readers and operates at a range up to 1m. It includes a custom low-noise, low power amplifier IC for processing the neural signal and an analog spike detection circuit for reducing digital computational requirements and communications bandwidth. Our system monitors the neural signal and periodically transmits the spike density in a user-programmable time window. The entire system draws an average 20 muA from the harvested 1.8V supply.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116208590","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":"Adaptive detection of action potentials using ultra low-power CMOS circuits","authors":"B. Gosselin, M. Sawan","doi":"10.1109/BIOCAS.2008.4696911","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696911","url":null,"abstract":"We present ultra low-power CMOS analog circuits for automatic detection of action potentials (APs). The proposed detection strategy locates AP waveforms and completely preserves their integrity. An adaptive threshold is implemented using a local time-averaging filter presenting a large time constant. The filter uses very small transconductances implemented by means of dedicated circuit techniques and subthreshold operation of MOS transistors. Also, a compact voltage squarer pre-processor is introduced to emphasize neural APs prior to detection. The proposed circuits were implemented in a CMOS 0.18-mum process and achieve ultra low-power consumption. Both circuits have been validated in simulations with synthetic neural waveforms. The adaptive threshold circuit dissipates only 27.2 nW, whereas the voltage squarer dissipates 76.7 nW.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114548797","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":"High-integrated microvalve for Lab-on-chip biomedical applications","authors":"M. Moreno, C. Aracil, J. Quero","doi":"10.1109/BIOCAS.2008.4696937","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696937","url":null,"abstract":"This paper presents a single-use fluid microvalve for lab-on-chip (LOC) applications that combines printed circuit board and SU-8 technologies. The main advantage of this device lies in the simplicity and low cost of the fabrication process. The operation of the valve consists in extracting a certain quantity of fluid by mechanical phenomenon when a membrane is melt by a resistor. The design is conceived to be integrated in an array composed by microneedles modules and biosensing devices. Integration of the microvalve has been maximized with the planar layout presented here. With this merge of technologies is possible to include microfluidics and electronics in the same LOC device, which is intended to biomedical applications. Experimental results that show the microvalve performance are presented.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121640542","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}
M. Abbod, J. Shieh, J. Yeh, K. Cheng, S.J. Huang, Y.Y. Han
{"title":"Intelligent systems for the prediction of Brain Death Index","authors":"M. Abbod, J. Shieh, J. Yeh, K. Cheng, S.J. Huang, Y.Y. Han","doi":"10.1109/BIOCAS.2008.4696896","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696896","url":null,"abstract":"New techniques to enable the prediction of a reliable brain death index (BDI) measures are needed to improve patient care in the intensive care unit (ICU). The utilization of robust indicators combined with improved methods of data analysis and modeling is likely to deliver this facility. Like many forms of indicators, a combination of different measurement types can always improve the assessment accuracy. Doctors can manage by a combination of local indicators and signal of heart rhythm to decide the BDI of neurosurgical and traumatized patients. New techniques for the prediction are needed as statistical analysis has a poor accuracy and is not applicable to the individual. artificial intelligence (AI) may provide these suitable methods. Artificial neural networks (ANN), the best-studied form of AI, has been used successfully, and can be used to model the patient BDI based on multi-input measurements from the patient. A multi-layer perception (MLP) and ensembled neural networks are chosen to be the network type of BDI model. This model can provide medical staffs a reference index to evaluate the status of IAC and brain death patients.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125630237","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":"VLSI-friendly algorithm for real-time spike sorting in Brain Machine Interface applications","authors":"F. Abu-Nimeh, M. Aghagolzadeh, K. Oweiss","doi":"10.1109/BIOCAS.2008.4696925","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696925","url":null,"abstract":"Recent research in brain machine interface (BMI) has shown that cortical implants can record and wirelessly transmit neural activity to external workstations for further processing, spike sorting, and decoding. In order to reduce complexity, bandwidth, and power consumption of such systems we introduce a miniaturized real-time spike sorting VLSI architecture that is to very low signal-to-noise ratios (SNR). This completely eliminates any external spike sorting dependencies, thus, bringing the entire system one step closer to be all integrated and fully implanted. The algorithm used in this architecture exploits three features to achieve better classification and real-time sorting: the spatial neuronal distribution across electrodes, the temporal and spectral information in the spike waveforms from individual neurons, and hardware limitations imposed by the size of the implant.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130603430","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":"Towards fault-tolerant digital microfluidic lab-on-chip: Defects, fault modeling, testing, and reconfiguration","authors":"K. Chakrabarty","doi":"10.1109/BIOCAS.2008.4696941","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696941","url":null,"abstract":"Dependability is an important attribute for microfluidic lab-on-chip devices that are being developed for safety-critical applications such as point-of-care health assessment, air-quality monitoring, and food-safety testing. Therefore, these devices must be adequately tested after manufacture and during bioassay operations. This paper presents a survey of early work on fault tolerance in digital microfluidic lab-on-chip systems. Defects are related to logical fault models that can be viewed not only in terms of traditional shorts and opens, but which also target biochip functionality. Based on these fault models, test techniques for lab-on-chip devices and digital microfluidic modules are presented.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132447143","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}