Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974201
D. Venuto, J. Rabaey
A SpV-resolution RFID ECoG data reader bas been designed and implemented in 65nm CMOS TSMC technology. The area occupancy is 1.8mm×l.9mm. In this paper, the design and measurement results are shown. The circuit average power consumption is less than 36μW for the analog part while the peak power of the digital one is 19mW (including the output buffers and protections) with supply of 1.2V, providing power transmission 300MHz by a class Ε PA. The data coming from 1MHz from the tag modulates the AC power and the envelope detector allow the acquisition. The asynchronous demodulation achieves a BER less than 10−6. The novelty of the solution and the experimental measurements propose the architecture as a pioneer for the ECoG reading out architecture.
{"title":"Design and characterization of a 65nm CMOS wireless RFID reader for ECoG tag","authors":"D. Venuto, J. Rabaey","doi":"10.1109/IWASI.2017.7974201","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974201","url":null,"abstract":"A SpV-resolution RFID ECoG data reader bas been designed and implemented in 65nm CMOS TSMC technology. The area occupancy is 1.8mm×l.9mm. In this paper, the design and measurement results are shown. The circuit average power consumption is less than 36μW for the analog part while the peak power of the digital one is 19mW (including the output buffers and protections) with supply of 1.2V, providing power transmission 300MHz by a class Ε PA. The data coming from 1MHz from the tag modulates the AC power and the envelope detector allow the acquisition. The asynchronous demodulation achieves a BER less than 10−6. The novelty of the solution and the experimental measurements propose the architecture as a pioneer for the ECoG reading out architecture.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125245961","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974246
Long Xu, J. Huijsing, K. Makinwa
This paper presents an NPN-based temperature sensor intended for the temperature compensation of the metal shunt resistor of an integrated current sensing system. The sensor was implemented in a 0.18 HV BCD CMOS technology and occupies 0.16mm2 After a one-point trim, its inaccuracy is less than ±0.4°C over the industrial temperature range (−40°C to 85°C). It also achieves 14.8niK resolution in a 7ms conversion time while consuming 12μm. This results in a resolution FOM of 18.4pJ·K2 the lowest ever reported for an NPN-based sensor.
{"title":"A 12μW NPN-based temperature sensor with a 18.4pJ K2 FOM in 0.18μm BCD CMOS","authors":"Long Xu, J. Huijsing, K. Makinwa","doi":"10.1109/IWASI.2017.7974246","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974246","url":null,"abstract":"This paper presents an NPN-based temperature sensor intended for the temperature compensation of the metal shunt resistor of an integrated current sensing system. The sensor was implemented in a 0.18 HV BCD CMOS technology and occupies 0.16mm<sup>2</sup> After a one-point trim, its inaccuracy is less than ±0.4°C over the industrial temperature range (−40°C to 85°C). It also achieves 14.8niK resolution in a 7ms conversion time while consuming 12μm. This results in a resolution FOM of 18.4pJ·K<sup>2</sup> the lowest ever reported for an NPN-based sensor.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122326996","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974259
J. Ohta
Recently, combination of genetic engineering and optical technology enables to measure and control biological functions with light. Fluorescent protein such as GFP can be used as an optical tag of a specific molecule, and photoactive protein such as ChR2 can be applied for optical manipulation of biological functions. This presentation introduces some kinds of implantable optical devices for measuring and controlling biological functions in the brain of a freely-moving rodent. Future direction is addressed for achieving bidirectional optical communication with brain.
{"title":"Optical sensor and interface technologies for implantable biomedical devices","authors":"J. Ohta","doi":"10.1109/IWASI.2017.7974259","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974259","url":null,"abstract":"Recently, combination of genetic engineering and optical technology enables to measure and control biological functions with light. Fluorescent protein such as GFP can be used as an optical tag of a specific molecule, and photoactive protein such as ChR2 can be applied for optical manipulation of biological functions. This presentation introduces some kinds of implantable optical devices for measuring and controlling biological functions in the brain of a freely-moving rodent. Future direction is addressed for achieving bidirectional optical communication with brain.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128098753","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974233
Soonyoung Cha, L. Milor
With aggressive scaling of silicon technology, integrated circuits (ICs) yield has emerged as a prominent concern. Yield loss comes from timing problems induced by process variations introduced by inaccuracy in nano-scale CMOS fabrication. To address this concern, we have developed a system to assist in optimizing yield and power. The system consists of timing violation sensors, clock duty-cycle controllers, and dynamic voltage scaling techniques to avoid timing violations and to reduce the supply voltage as much as possible. By using failure probability maps, we evaluate the yield and performance enhancement of an example microprocessor system.
{"title":"Adaptive supply voltage and duty cycle controller for yield-power optimization of ICs","authors":"Soonyoung Cha, L. Milor","doi":"10.1109/IWASI.2017.7974233","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974233","url":null,"abstract":"With aggressive scaling of silicon technology, integrated circuits (ICs) yield has emerged as a prominent concern. Yield loss comes from timing problems induced by process variations introduced by inaccuracy in nano-scale CMOS fabrication. To address this concern, we have developed a system to assist in optimizing yield and power. The system consists of timing violation sensors, clock duty-cycle controllers, and dynamic voltage scaling techniques to avoid timing violations and to reduce the supply voltage as much as possible. By using failure probability maps, we evaluate the yield and performance enhancement of an example microprocessor system.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121232280","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974205
J. Rabaey, Abbas Rahimi, Sohum Datta, M. Rusch, P. Kanerva, B. Olshausen
Some of most compelling application domains of the IoT and Swarm concepts relate to how humans interact with the world around it and the cyberworld beyond. While the proliferation of communication and data processing devices has profoundly altered our interaction patterns, little has been changed in the way we process inputs (sensory) and outputs (actuation). The combination of IoT (Swarms) and wearable devices offers the potential for changing all of this, opening the door for true human augmentation. The epitome of this would be a direct interface to the human brain. Yet, making sense of the plethora of information received from the often noisy sensors and making reliable decisions within very tight latency bounds (< 10 ms) typically demands huge computational workloads to be performed in wearable form factors at extreme energy efficiency. In this presentation, we will make the case why alternative non-Von Neumann computational paradigms and architectures may be the right choice for these cognitive processing tasks. Even more, we will focus on a computational model called Hyper-Dimensional Computing (HDC), and illustrate with concrete examples of why this approach may be the right one in a post-Moore data-driven arena.
{"title":"Human-centric computing — The case for a Hyper-Dimensional approach","authors":"J. Rabaey, Abbas Rahimi, Sohum Datta, M. Rusch, P. Kanerva, B. Olshausen","doi":"10.1109/IWASI.2017.7974205","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974205","url":null,"abstract":"Some of most compelling application domains of the IoT and Swarm concepts relate to how humans interact with the world around it and the cyberworld beyond. While the proliferation of communication and data processing devices has profoundly altered our interaction patterns, little has been changed in the way we process inputs (sensory) and outputs (actuation). The combination of IoT (Swarms) and wearable devices offers the potential for changing all of this, opening the door for true human augmentation. The epitome of this would be a direct interface to the human brain. Yet, making sense of the plethora of information received from the often noisy sensors and making reliable decisions within very tight latency bounds (< 10 ms) typically demands huge computational workloads to be performed in wearable form factors at extreme energy efficiency. In this presentation, we will make the case why alternative non-Von Neumann computational paradigms and architectures may be the right choice for these cognitive processing tasks. Even more, we will focus on a computational model called Hyper-Dimensional Computing (HDC), and illustrate with concrete examples of why this approach may be the right one in a post-Moore data-driven arena.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126360864","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974243
T. Takano, Yohei Kawamura, H. Nakata
W-band 95GHz Doppler radar named FALCON-I was developed and operated for cloud observations. High spacial and high velocity resolution are achieved with low transmitting power of millimeter wave. FALCON-I can observe not only clouds and precipitations but also flying small objects such as birds, insects, seeds of plants, and volcanic ashes in the atmosphere.
{"title":"Performance of W-band FMCW Doppler radar FALCON-I as sensing system of atmosphere","authors":"T. Takano, Yohei Kawamura, H. Nakata","doi":"10.1109/IWASI.2017.7974243","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974243","url":null,"abstract":"W-band 95GHz Doppler radar named FALCON-I was developed and operated for cloud observations. High spacial and high velocity resolution are achieved with low transmitting power of millimeter wave. FALCON-I can observe not only clouds and precipitations but also flying small objects such as birds, insects, seeds of plants, and volcanic ashes in the atmosphere.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121792126","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974208
M. Magno, Michael Pritz, Philipp Mayer, L. Benini
Wearable smart sensing is a promising technology to enhance user experience that has already been exploited in sport/fitness, as well as health and human monitoring. Wearable sensing systems not only provide continuous data monitoring and acquisition, but are also expected to process, and make sense of the acquired data by classification in similar ways as human experts do. Supporting continuous operation on ultra-small batteries poses unique challenges in energy efficiency. In this paper, we present an ultra-low-power bracelet with several sensors that is able to run multi-layer neural networks learning algorithms to process data efficiently. The design combines low-power design, energy efficient algorithms and makes this bracelet suitable for long-term uninterrupted usage with small coin batteries. We demonstrate in-field measurement results that prove that neural networks applications can fit within the mW power and memory envelope of a commercial ARM Cortex M4F microcontroller. We show that a fully connected network of 26 neurons achieve an accuracy of 100% on emotion detection, using only 2% of memory available. Field trials demonstrate that the wearable device can achieve a 2-month lifetime while performing one emotion detection classification every 10 minutes.
{"title":"DeepEmote: Towards multi-layer neural networks in a low power wearable multi-sensors bracelet","authors":"M. Magno, Michael Pritz, Philipp Mayer, L. Benini","doi":"10.1109/IWASI.2017.7974208","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974208","url":null,"abstract":"Wearable smart sensing is a promising technology to enhance user experience that has already been exploited in sport/fitness, as well as health and human monitoring. Wearable sensing systems not only provide continuous data monitoring and acquisition, but are also expected to process, and make sense of the acquired data by classification in similar ways as human experts do. Supporting continuous operation on ultra-small batteries poses unique challenges in energy efficiency. In this paper, we present an ultra-low-power bracelet with several sensors that is able to run multi-layer neural networks learning algorithms to process data efficiently. The design combines low-power design, energy efficient algorithms and makes this bracelet suitable for long-term uninterrupted usage with small coin batteries. We demonstrate in-field measurement results that prove that neural networks applications can fit within the mW power and memory envelope of a commercial ARM Cortex M4F microcontroller. We show that a fully connected network of 26 neurons achieve an accuracy of 100% on emotion detection, using only 2% of memory available. Field trials demonstrate that the wearable device can achieve a 2-month lifetime while performing one emotion detection classification every 10 minutes.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129008642","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974203
M. Paun, V. Paun
This work is devoted to the modeling and analysis of the antennas in the cochlear implants. In order to accurately characterize the antenna, a three-dimensional model has been built, where precise dimensions of the loop antenna are given. The most important performance indicators have been numerically assessed. The total electric field three-dimensional polar representation is included. The radiation pattern. Smith charts and Smith contour plots are also obtained.
{"title":"Three-dimensional modeling and analysis of antennas in cochlear implants","authors":"M. Paun, V. Paun","doi":"10.1109/IWASI.2017.7974203","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974203","url":null,"abstract":"This work is devoted to the modeling and analysis of the antennas in the cochlear implants. In order to accurately characterize the antenna, a three-dimensional model has been built, where precise dimensions of the loop antenna are given. The most important performance indicators have been numerically assessed. The total electric field three-dimensional polar representation is included. The radiation pattern. Smith charts and Smith contour plots are also obtained.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128023164","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974242
D. Palossi, Jaskirat Singh, M. Magno, L. Benini
Unmanned Aerial Vehicles (UAVs) with high level autonomous navigation capabilities are a hot topic both in industry and academia due to their numerous applications. However, autonomous navigation algorithms are demanding from the computational standpoint, and it is very challenging to run them on-board of nano-scale UAVs (i.e., few centimeters of diameter) because of the limited capabilities of their MCU-based controllers. This work focuses on the object tracking capability, (i.e., target following capability) on such nano-UAVs. We present a lightweight hardware-software solution, bringing autonomous navigation on a commercial platform using only on-board computational resources. Furthermore, we evaluate a parallel ultra-low-power (PULP) platform that enables the execution of even more sophisticated algorithms. Experimental results demonstrate the benefits of our solution, achieving accurate target following using an ARM Cortex M4 microcontroller consuming ≈ 130mW. Our evaluation on a PULP architecture shows the proposed solution running up-to 60 frame-per second in a power envelope of ≈ 30mW leaving more than 70% of the computational resources free for further on-board processing of more complex algorithms.
{"title":"Target following on nano-scale Unmanned Aerial Vehicles","authors":"D. Palossi, Jaskirat Singh, M. Magno, L. Benini","doi":"10.1109/IWASI.2017.7974242","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974242","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) with high level autonomous navigation capabilities are a hot topic both in industry and academia due to their numerous applications. However, autonomous navigation algorithms are demanding from the computational standpoint, and it is very challenging to run them on-board of nano-scale UAVs (i.e., few centimeters of diameter) because of the limited capabilities of their MCU-based controllers. This work focuses on the object tracking capability, (i.e., target following capability) on such nano-UAVs. We present a lightweight hardware-software solution, bringing autonomous navigation on a commercial platform using only on-board computational resources. Furthermore, we evaluate a parallel ultra-low-power (PULP) platform that enables the execution of even more sophisticated algorithms. Experimental results demonstrate the benefits of our solution, achieving accurate target following using an ARM Cortex M4 microcontroller consuming ≈ 130mW. Our evaluation on a PULP architecture shows the proposed solution running up-to 60 frame-per second in a power envelope of ≈ 30mW leaving more than 70% of the computational resources free for further on-board processing of more complex algorithms.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121196187","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}
Pub Date : 2017-06-01DOI: 10.1109/IWASI.2017.7974219
N. Verma
Information technology has had profound impacts on our lives. The problem is that, so far, technology has required our explicit attention to provide services. This limits the scenarios in which it can or we would like it to take action. On the other hand, perceptive systems aim to understand our activities and intentions to proactively, collaboratively, and adaptively provide services. This requires systems to form projections of the world, but also construct models for how to respond. This talk starts by looking at how deploying large numbers of form-fitting sensors, which are explicitly associated with the physical objects we interact with (including each other), can provide contextually-relevant and structured data for enabling the construction of such models. Then, a possible platform technology for creating such sensors is examined, namely Large-Area Electronics (LAE). The challenges of realizing full systems from this are explored. In particular, perceptive systems present demanding functional requirements, but, through emerging algorithms from statistical signal processing and machine learning, also open up new opportunities for addressing technological limitations. Several LAE systems for human monitoring are presented, demonstrating the potentials.
{"title":"Covering our world with sensors","authors":"N. Verma","doi":"10.1109/IWASI.2017.7974219","DOIUrl":"https://doi.org/10.1109/IWASI.2017.7974219","url":null,"abstract":"Information technology has had profound impacts on our lives. The problem is that, so far, technology has required our explicit attention to provide services. This limits the scenarios in which it can or we would like it to take action. On the other hand, perceptive systems aim to understand our activities and intentions to proactively, collaboratively, and adaptively provide services. This requires systems to form projections of the world, but also construct models for how to respond. This talk starts by looking at how deploying large numbers of form-fitting sensors, which are explicitly associated with the physical objects we interact with (including each other), can provide contextually-relevant and structured data for enabling the construction of such models. Then, a possible platform technology for creating such sensors is examined, namely Large-Area Electronics (LAE). The challenges of realizing full systems from this are explored. In particular, perceptive systems present demanding functional requirements, but, through emerging algorithms from statistical signal processing and machine learning, also open up new opportunities for addressing technological limitations. Several LAE systems for human monitoring are presented, demonstrating the potentials.","PeriodicalId":332606,"journal":{"name":"2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116804118","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}
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