... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks最新文献
Pub Date : 2023-10-01Epub Date: 2023-12-01DOI: 10.1109/BSN58485.2023.10330912
Charlotte E Goldfine, Hannah Albrechta, Conall O'Cleirigh, Adam Standley, Yassir Mohamed, Joanne Hokayem, Jasper S Lee, T Christopher Carnes, Georgia R Goodman, Kenneth H Mayer, Pamela Alpert, Peter R Chai
Adherence to medications is a complex task that requires complex biobehavioral support. To better provide tools to assist with medication adherence, digital pills provide an option to directly measure medication taking behaviors. These systems comprise a gelatin capsule with radiofrequency emitter, a wearable Reader that collects the radio signal and a smartphone app that collects ingestion data displays it for patients and clinicians. These systems are feasible in measuring adherence in the real-world, even in stigmatized diseases like HIV treatment adherence. While the current iteration of the digital pill system utilizes a wearable Reader worn like a necklace, preliminary feedback demonstrated that a miniaturized system that was worn on the wrist could be more functional in the real-world. This paper therefore describes the development and preliminary field testing of a wrist-borne wearable Reader to facilitate acquisition of oral HIV pre-exposure prophylaxis (PrEP) adherence data among individual prescribed PrEP.
{"title":"Preliminary feasibility of a wrist-worn receiver to measure medication adherence via an ingestible radiofrequency sensor.","authors":"Charlotte E Goldfine, Hannah Albrechta, Conall O'Cleirigh, Adam Standley, Yassir Mohamed, Joanne Hokayem, Jasper S Lee, T Christopher Carnes, Georgia R Goodman, Kenneth H Mayer, Pamela Alpert, Peter R Chai","doi":"10.1109/BSN58485.2023.10330912","DOIUrl":"10.1109/BSN58485.2023.10330912","url":null,"abstract":"<p><p>Adherence to medications is a complex task that requires complex biobehavioral support. To better provide tools to assist with medication adherence, digital pills provide an option to directly measure medication taking behaviors. These systems comprise a gelatin capsule with radiofrequency emitter, a wearable Reader that collects the radio signal and a smartphone app that collects ingestion data displays it for patients and clinicians. These systems are feasible in measuring adherence in the real-world, even in stigmatized diseases like HIV treatment adherence. While the current iteration of the digital pill system utilizes a wearable Reader worn like a necklace, preliminary feedback demonstrated that a miniaturized system that was worn on the wrist could be more functional in the real-world. This paper therefore describes the development and preliminary field testing of a wrist-borne wearable Reader to facilitate acquisition of oral HIV pre-exposure prophylaxis (PrEP) adherence data among individual prescribed PrEP.</p>","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"2023 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10753620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139059212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01Epub Date: 2023-12-01DOI: 10.1109/bsn58485.2023.10331378
Zhiyuan Wang, Mark Rucker, Emma R Toner, Maria A Larrazabal, Mehdi Boukhechba, Bethany A Teachman, Laura E Barnes
Wearable devices with embedded sensors can provide personalized healthcare and wellness benefits in digital phenotyping and adaptive interventions. However, the collection, storage, and transmission of biometric data (including processed features rather than raw signals) from these devices pose significant privacy concerns. This quantitative, data-driven study examines the privacy risks associated with wearable-based digital phenotyping practices, with a focus on user reidentification (ReID), which is the process of identifying participants' IDs from deidentified digital phenotyping datasets. We propose a machine-learning-based computational pipeline to evaluate and quantify model outcomes under various configurations, such as modality inclusion, window length, and feature type and format, to investigate the factors influencing ReID risks and their predictive trade-offs. This pipeline leverages features extracted from three wearable sensors, resulting in up to 68.43% accuracy in ReID risk for a sample size of N=45 socially anxious participants based on only descriptive features of 10-second observations. Additionally, we explore the trade-offs between privacy risks and predictive benefits by adjusting various settings (e.g., the ways to process extracted features). Our findings highlight the importance of privacy in digital phenotyping and suggest potential future directions.
{"title":"Understanding Privacy Risks versus Predictive Benefits in Wearable Sensor-Based Digital Phenotyping: A Quantitative Cost-Benefit Analysis.","authors":"Zhiyuan Wang, Mark Rucker, Emma R Toner, Maria A Larrazabal, Mehdi Boukhechba, Bethany A Teachman, Laura E Barnes","doi":"10.1109/bsn58485.2023.10331378","DOIUrl":"10.1109/bsn58485.2023.10331378","url":null,"abstract":"<p><p>Wearable devices with embedded sensors can provide personalized healthcare and wellness benefits in digital phenotyping and adaptive interventions. However, the collection, storage, and transmission of biometric data (including processed features rather than raw signals) from these devices pose significant privacy concerns. This quantitative, data-driven study examines the privacy risks associated with wearable-based digital phenotyping practices, with a focus on user <i>reidentification (ReID)</i>, which is the process of identifying participants' IDs from deidentified digital phenotyping datasets. We propose a machine-learning-based computational pipeline to evaluate and quantify model outcomes under various configurations, such as <i>modality inclusion</i>, <i>window length</i>, and <i>feature type and format</i>, to investigate the factors influencing ReID risks and their predictive trade-offs. This pipeline leverages features extracted from three wearable sensors, resulting in up to 68.43% accuracy in ReID risk for a sample size of N=45 socially anxious participants based on only descriptive features of 10-second observations. Additionally, we explore the trade-offs between privacy risks and predictive benefits by adjusting various settings (e.g., the ways to process extracted features). Our findings highlight the importance of privacy in digital phenotyping and suggest potential future directions.</p>","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"2023 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11581184/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01Epub Date: 2023-12-01DOI: 10.1109/bsn58485.2023.10331081
Sina Razaghi, Ebenezer Asabre, Abu Bony Amin, Yeonsik Noh
Bio-impedance spectroscopy (BIS) is a sophisticated testing technique used to analyze impedance changes at different frequencies. In this study, we investigated the estimation of the Cole Model for BIS measurements without the need for high-frequency resistance and reactance measurements, where they are inaccurate due to leakage capacitences. We employed a Texas Instruments evaluation kit (AFE4300) and compared the Cole plots of two different circuit models of tissue between the proposed configuration and a commercial impedance analyzer used as a reference. To enhance the performance of the AFE4300, we incorporated an external direct digital synthesis (DDS) to generate higher frequencies. The results demonstrated the reliability of the proposed theoretical estimation technique in accurately estimating the resistances and capacitance of the Cole Model.
生物阻抗光谱（BIS）是一种复杂的测试技术，用于分析不同频率下的阻抗变化。在本研究中，我们研究了如何利用科尔模型估算 BIS 测量值，而无需进行高频电阻和电抗测量，因为高频电阻和电抗测量会因泄漏电容而不准确。我们使用了德州仪器公司的评估套件（AFE4300），并比较了拟议配置与用作参考的商用阻抗分析仪之间两种不同组织电路模型的科尔图。为了提高 AFE4300 的性能，我们采用了外部直接数字合成 (DDS) 来产生更高的频率。结果表明，所提出的理论估算技术在准确估算科尔模型的电阻和电容方面非常可靠。
{"title":"A New Technique to Estimate the Cole Model for Bio-impedance Spectroscopy with the High-Frequency Characteristics Estimation.","authors":"Sina Razaghi, Ebenezer Asabre, Abu Bony Amin, Yeonsik Noh","doi":"10.1109/bsn58485.2023.10331081","DOIUrl":"10.1109/bsn58485.2023.10331081","url":null,"abstract":"<p><p>Bio-impedance spectroscopy (BIS) is a sophisticated testing technique used to analyze impedance changes at different frequencies. In this study, we investigated the estimation of the Cole Model for BIS measurements without the need for high-frequency resistance and reactance measurements, where they are inaccurate due to leakage capacitences. We employed a Texas Instruments evaluation kit (AFE4300) and compared the Cole plots of two different circuit models of tissue between the proposed configuration and a commercial impedance analyzer used as a reference. To enhance the performance of the AFE4300, we incorporated an external direct digital synthesis (DDS) to generate higher frequencies. The results demonstrated the reliability of the proposed theoretical estimation technique in accurately estimating the resistances and capacitance of the Cole Model.</p>","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"2023 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095251/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140945558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-06DOI: 10.5220/0011692900003399
David Ding, Ivan Carvalho, R. Lawrence
Efficiently querying data on embedded sensor and IoT devices is challenging given the very limited memory and CPU resources. With the increasing volumes of collected data, it is critical to process, filter, and manipulate data on the edge devices where it is collected to improve efficiency and reduce network transmissions. Existing embedded index structures do not adapt to the data distribution and characteristics. This paper demonstrates how applying learned indexes that develop space efficient summaries of the data can dramatically improve the query performance and predictability. Learned indexes based on linear approximations can reduce the query I/O by 50 to 90% and improve query throughput by a factor of 2 to 5, while only requiring a few kilobytes of RAM. Experimental results on a variety of time series data sets demonstrate the advantages of learned indexes that considerably improve over the state-of-the-art index algorithms.
{"title":"Using Learned Indexes to Improve Time Series Indexing Performance on Embedded Sensor Devices","authors":"David Ding, Ivan Carvalho, R. Lawrence","doi":"10.5220/0011692900003399","DOIUrl":"https://doi.org/10.5220/0011692900003399","url":null,"abstract":"Efficiently querying data on embedded sensor and IoT devices is challenging given the very limited memory and CPU resources. With the increasing volumes of collected data, it is critical to process, filter, and manipulate data on the edge devices where it is collected to improve efficiency and reduce network transmissions. Existing embedded index structures do not adapt to the data distribution and characteristics. This paper demonstrates how applying learned indexes that develop space efficient summaries of the data can dramatically improve the query performance and predictability. Learned indexes based on linear approximations can reduce the query I/O by 50 to 90% and improve query throughput by a factor of 2 to 5, while only requiring a few kilobytes of RAM. Experimental results on a variety of time series data sets demonstrate the advantages of learned indexes that considerably improve over the state-of-the-art index algorithms.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"6 1","pages":"23-31"},"PeriodicalIF":0.0,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77635493","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 : 2023-01-01DOI: 10.5220/0011692100003399
Mattia Ragnoli, A. Leoni, G. Barile, V. Stornelli, G. Ferri
{"title":"LoRa Structural Monitoring Wireless Sensor Networks","authors":"Mattia Ragnoli, A. Leoni, G. Barile, V. Stornelli, G. Ferri","doi":"10.5220/0011692100003399","DOIUrl":"https://doi.org/10.5220/0011692100003399","url":null,"abstract":"","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"2016 1","pages":"79-86"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83128044","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 : 2023-01-01DOI: 10.5220/0011828700003399
M. Khatun, Mark Liske, Rolf Jung, Michael Glass
{"title":"A Simulation-Based Testing to Evaluate and Improve a Radar Sensor Performance in a Use Case of Highly Automated Driving Systems","authors":"M. Khatun, Mark Liske, Rolf Jung, Michael Glass","doi":"10.5220/0011828700003399","DOIUrl":"https://doi.org/10.5220/0011828700003399","url":null,"abstract":"","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"73 1","pages":"42-53"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84249645","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 : 2023-01-01DOI: 10.5220/0011791200003399
Simon Thelen, Klaus Volbert, D. Nunes
{"title":"A Survey on Algorithmic Problems in Wireless Systems","authors":"Simon Thelen, Klaus Volbert, D. Nunes","doi":"10.5220/0011791200003399","DOIUrl":"https://doi.org/10.5220/0011791200003399","url":null,"abstract":"","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"1 1","pages":"101-111"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91054202","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 : 2023-01-01DOI: 10.5220/0011777000003399
Batuhan Can, Halit Uyanık, T. Ovatman
: This paper proposes two different approaches to be applied in gateway placement problem in LoRaWAN sensor networks. The first approach is based on finding the minimal set to contain all the coverage intersections of the sensors and the second approach is based on optimization via integer programming over the distance between the gateways and sensors. Our results show that using automated gateway placement provides significantly less number of gateways to be used.
{"title":"Gateway Placement in LoRaWAN Enabled Sensor Networks","authors":"Batuhan Can, Halit Uyanık, T. Ovatman","doi":"10.5220/0011777000003399","DOIUrl":"https://doi.org/10.5220/0011777000003399","url":null,"abstract":": This paper proposes two different approaches to be applied in gateway placement problem in LoRaWAN sensor networks. The first approach is based on finding the minimal set to contain all the coverage intersections of the sensors and the second approach is based on optimization via integer programming over the distance between the gateways and sensors. Our results show that using automated gateway placement provides significantly less number of gateways to be used.","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"9 1","pages":"93-100"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82778490","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 : 2023-01-01DOI: 10.5220/0011747400003399
J. Grabis, R. Pirta-Dreimane, Brigita Dejus, A. Borodinecs, Rolands Zaharovs
{"title":"Triple Pi Sensing to Limit Spread of Infectious Diseases at Workplace","authors":"J. Grabis, R. Pirta-Dreimane, Brigita Dejus, A. Borodinecs, Rolands Zaharovs","doi":"10.5220/0011747400003399","DOIUrl":"https://doi.org/10.5220/0011747400003399","url":null,"abstract":"","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"17 1","pages":"87-92"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74650355","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 : 2023-01-01DOI: 10.5220/0011688300003399
Marco Manso, B. Guerra, Fernando Freire, R. Chirico, N. Liberatore, Renea Linder, Ulrike Schröder, Yusuf Yilmaz
{"title":"On the Path Towards Standardisation of a Sensor API for Forensics Investigations","authors":"Marco Manso, B. Guerra, Fernando Freire, R. Chirico, N. Liberatore, Renea Linder, Ulrike Schröder, Yusuf Yilmaz","doi":"10.5220/0011688300003399","DOIUrl":"https://doi.org/10.5220/0011688300003399","url":null,"abstract":"","PeriodicalId":72028,"journal":{"name":"... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks","volume":"23 1","pages":"15-22"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77616614","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}
... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks
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