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Abstract
Opioid use disorder is a growing public health concern in the United States, causing economic burden and hindered by stigma. New forms of data, including location data, may improve the effectiveness of interventions for preventing and treating opioid use disorder and/or misuse, increase access to treatment and address racial and ethnic disparities. This qualitative study aimed to identify factors that contribute to users' experience with a publicly available location-tracking mobile app - and investigate their privacy and ethical concerns. The study was conducted through two 15-minute interviews within a 48-h time frame. Participants were recruited from a pool of past research participants, Facebook ads, and referrals, and had to meet certain inclusion criteria related to opioid use disorder and/or misuse. The study had a final sample of 30 participants, 15 male and 15 female. The study suggests that a simple onboarding process and convenient experience can enhance participant adherence to the study app and other similar location-based research apps. However, the study also found that participants had concerns about privacy and transparency about locational privacy when sharing their location data. To improve the app, researchers suggest incorporating user behavior earlier in the app development stage. The study also highlights the importance of addressing ethical and privacy concerns such as limiting the types of collected data, incorporating data encryption and retention strategies, giving access to research staff only, and not sharing the data with third-party companies or law enforcement agencies to increase user satisfaction.
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Affiliation(s)
- Maryam Hassani
- Department of Informatics, University of California, Irvine, California, USA
| | - Sean D Young
- Department of Informatics, University of California, Irvine, California, USA
- Department of Emergency Medicine, University of California, Irvine, California, USA
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2
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Ogasawara T, Mukaino M, Matsunaga K, Wada Y, Suzuki T, Aoshima Y, Furuzawa S, Kono Y, Saitoh E, Yamaguchi M, Otaka Y, Tsukada S. Prediction of stroke patients' bedroom-stay duration: machine-learning approach using wearable sensor data. Front Bioeng Biotechnol 2024; 11:1285945. [PMID: 38234303 PMCID: PMC10791943 DOI: 10.3389/fbioe.2023.1285945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024] Open
Abstract
Background: The importance of being physically active and avoiding staying in bed has been recognized in stroke rehabilitation. However, studies have pointed out that stroke patients admitted to rehabilitation units often spend most of their day immobile and inactive, with limited opportunities for activity outside their bedrooms. To address this issue, it is necessary to record the duration of stroke patients staying in their bedrooms, but it is impractical for medical providers to do this manually during their daily work of providing care. Although an automated approach using wearable devices and access points is more practical, implementing these access points into medical facilities is costly. However, when combined with machine learning, predicting the duration of stroke patients staying in their bedrooms is possible with reduced cost. We assessed using machine learning to estimate bedroom-stay duration using activity data recorded with wearable devices. Method: We recruited 99 stroke hemiparesis inpatients and conducted 343 measurements. Data on electrocardiograms and chest acceleration were measured using a wearable device, and the location name of the access point that detected the signal of the device was recorded. We first investigated the correlation between bedroom-stay duration measured from the access point as the objective variable and activity data measured with a wearable device and demographic information as explanatory variables. To evaluate the duration predictability, we then compared machine-learning models commonly used in medical studies. Results: We conducted 228 measurements that surpassed a 90% data-acquisition rate using Bluetooth Low Energy. Among the explanatory variables, the period spent reclining and sitting/standing were correlated with bedroom-stay duration (Spearman's rank correlation coefficient (R) of 0.56 and -0.52, p < 0.001). Interestingly, the sum of the motor and cognitive categories of the functional independence measure, clinical indicators of the abilities of stroke patients, lacked correlation. The correlation between the actual bedroom-stay duration and predicted one using machine-learning models resulted in an R of 0.72 and p < 0.001, suggesting the possibility of predicting bedroom-stay duration from activity data and demographics. Conclusion: Wearable devices, coupled with machine learning, can predict the duration of patients staying in their bedrooms. Once trained, the machine-learning model can predict without continuously tracking the actual location, enabling more cost-effective and privacy-centric future measurements.
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Affiliation(s)
- Takayuki Ogasawara
- NTT Basic Research Laboratories and Bio-Medical Informatics Research Center, NTT Corporation, Atsugi, Japan
- Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan
| | - Masahiko Mukaino
- Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan
- Department of Rehabilitation Medicine, Hokkaido University Hospital, Sapporo, Japan
| | | | - Yoshitaka Wada
- Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan
| | - Takuya Suzuki
- Department of Rehabilitation Medicine, Fujita Health University Hospital, Toyoake, Japan
| | - Yasushi Aoshima
- Department of Rehabilitation Medicine, Fujita Health University Hospital, Toyoake, Japan
| | - Shotaro Furuzawa
- Department of Rehabilitation Medicine, Fujita Health University Hospital, Toyoake, Japan
| | - Yuji Kono
- Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan
- Department of Rehabilitation Medicine, Fujita Health University Hospital, Toyoake, Japan
| | - Eiichi Saitoh
- Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan
| | - Masumi Yamaguchi
- NTT Basic Research Laboratories and Bio-Medical Informatics Research Center, NTT Corporation, Atsugi, Japan
| | - Yohei Otaka
- Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan
| | - Shingo Tsukada
- NTT Basic Research Laboratories and Bio-Medical Informatics Research Center, NTT Corporation, Atsugi, Japan
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3
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Zhang Y, Clark WW, Tillman B, Chun YJ, Liu S, Cho SK. A System to Track Stent Location in the Human Body by Fusing Magnetometer and Accelerometer Measurements. Sensors (Basel) 2023; 23:4887. [PMID: 37430804 PMCID: PMC10222797 DOI: 10.3390/s23104887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/09/2023] [Accepted: 05/10/2023] [Indexed: 07/12/2023]
Abstract
This paper will introduce a simple locating system to track a stent when it is deployed into a human artery. The stent is proposed to achieve hemostasis for bleeding soldiers on the battlefield, where common surgical imaging equipment such as fluoroscopy systems are not available. In the application of interest, the stent must be guided to the right location to avoid serious complications. The most important features are its relative accuracy and the ease by which it may be quickly set up and used in a trauma situation. The locating approach in this paper utilizes a magnet outside the human body as the reference and a magnetometer that will be deployed inside the artery with the stent. The sensor can detect its location in a coordinate system centered with the reference magnet. In practice, the main challenge is that the locating accuracy will be deteriorated by external magnetic interference, rotation of the sensor, and random noise. These causes of error are addressed in the paper to improve the locating accuracy and repeatability under various conditions. Finally, the system's locating performance will be validated in benchtop experiments, where the effects of the disturbance-eliminating procedures will be addressed.
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Affiliation(s)
- Yifan Zhang
- Mechanical Engineering and Materials Science Department, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - William W. Clark
- Mechanical Engineering and Materials Science Department, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Bryan Tillman
- Vascular Surgery, The Ohio State University, Columbus, OH 43210, USA
| | - Young Jae Chun
- Industrial Engineering Department, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Stephanie Liu
- Mechanical Engineering and Materials Science Department, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Sung Kwon Cho
- Mechanical Engineering and Materials Science Department, University of Pittsburgh, Pittsburgh, PA 15261, USA
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Babaghayou M, Chaib N, Lagraa N, Ferrag MA, Maglaras L. A Safety-Aware Location Privacy-Preserving IoV Scheme with Road Congestion-Estimation in Mobile Edge Computing. Sensors (Basel) 2023; 23:531. [PMID: 36617126 PMCID: PMC9823413 DOI: 10.3390/s23010531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/26/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
By leveraging the conventional Vehicular Ad-hoc Networks (VANETs), the Internet of Vehicles (IoV) paradigm has attracted the attention of different research and development bodies. However, IoV deployment is still at stake as many security and privacy issues are looming; location tracking using overheard safety messages is a good example of such issues. In the context of location privacy, many schemes have been deployed to mitigate the adversary's exploiting abilities. The most appealing schemes are those using the silent period feature, since they provide an acceptable level of privacy. Unfortunately, the cost of silent periods in most schemes is the trade-off between privacy and safety, as these schemes do not consider the timing of silent periods from the perspective of safety. In this paper, and by exploiting the nature of public transport and role vehicles (overseers), we propose a novel location privacy scheme, called OVR, that uses the silent period feature by letting the overseers ensure safety and allowing other vehicles to enter into silence mode, thus enhancing their location privacy. This scheme is inspired by the well-known war strategy "Give up a Pawn to Save a Chariot". Additionally, the scheme does support road congestion estimation in real time by enabling the estimation locally on their On-Board Units that act as mobile edge servers and deliver these data to a static edge server that is implemented at the cell tower or road-side unit level, which boosts the connectivity and reduces network latencies. When OVR is compared with other schemes in urban and highway models, the overall results show its beneficial use.
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Affiliation(s)
| | | | | | - Mohamed Amine Ferrag
- Technology Innovation Institute, Masdar City 9639, Abu Dhabi, United Arab Emirates
| | - Leandros Maglaras
- Blockpass ID Lab., Edinburgh Napier University, Edinburgh EH10 5DT, UK
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Chung J, Brakey HR, Reeder B, Myers O, Demiris G. Community-dwelling older adults' acceptance of smartwatches for health and location tracking. Int J Older People Nurs 2023; 18:e12490. [PMID: 35818900 PMCID: PMC10078487 DOI: 10.1111/opn.12490] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 06/23/2022] [Accepted: 06/27/2022] [Indexed: 01/13/2023]
Abstract
BACKGROUND Despite rapid growth in the popularity of smartwatches, evidence lacks regarding older adults' acceptance of smartwatches. Since most wearable sensors are not designed specifically for older adults, there is a need to examine wearability and usability challenges of wearable sensing devices faced by older adults to facilitate the use of objective measurements of health and mobility. OBJECTIVES We aimed to examine older adults' perceptions of GPS-enabled smartwatches and to identify potential barriers and facilitators of smartwatch and sensor data use. METHODS As part of a larger feasibility study, we conducted a mixed-methods study that included a descriptive content analysis of interviews and a brief usability survey with 30 participants aged 60 years and older after they had used a smartwatch for 3 days. RESULTS Most participants perceived wearable activity trackers including smartwatches and sensor-based data as useful for tracking health, finding activity patterns and promoting healthy behaviours. Privacy was of little concern, leading to willingness to share activity and location data with others. Participants identified barriers to usability as clumsy design, lack of aesthetic appeal, and difficulty reading the display and using the GPS tracking function. In contrast, identified facilitators of adoption included a big display, high-tech look, self-awareness and possible behaviour change. CONCLUSIONS Smartwatches have the potential of personalised detection of health deterioration and disability prevention, based on analysis of older adults' activities in free-living environments. The usefulness of this technology for older adults can be significantly increased by addressing usability issues and providing instructions on challenging features. IMPLICATIONS FOR PRACTICE To support sustained self-monitoring behaviours through wearable sensor devices in older adults, it is critical to examine how they perceive those devices and identify factors affecting technology acceptance that can maximise adoption.
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Affiliation(s)
- Jane Chung
- Virginia Commonwealth University School of Nursing, Richmond, Virginia, USA
| | - Heidi Rishel Brakey
- Clinical and Translational Science Center, University of New Mexico, Albuquerque, New Mexico, USA
| | - Blaine Reeder
- University of Missouri School of Nursing, Columbia, Missouri, USA.,University of Missouri Institute for Data Science & Informatics, Columbia, Missouri, USA
| | - Orrin Myers
- Department of Family and Community Medicine, School of Medicine, University of New Mexico, Albuquerque, New Mexico, USA
| | - George Demiris
- University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
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Abstract
In March 2020, Israel passed emergency regulations authorizing its internal security agency to track citizens' mobile phone geolocations in order to tackle the spread of COVID-19. This unprecedented surveillance enterprise attracted extensive media attention and sparked a vigorous public debate regarding technology and democratic values such as privacy, mobility, and control. This article examines press coverage of Israel's surveillance of its citizens during the COVID-19 pandemic by four leading news sites to identify and map the frames that informed their reports. Based on a thematic analysis, our findings point to supportive and critical constructions of mobile phone location-tracking and organize them within two scapes: personal; and international. These attest to the collective imagining of intimacies and public life, respectively. We draw on the case study to articulate mobile phones as devices that reduce movement into manageable mapped information and individuals into controllable data. Mobile phone location-tracking during the COVID-19 pandemic is understood as turning mobility into order and control.
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Affiliation(s)
- Aya Yadlin
- Aya Yadlin, Department of Politics and
Communication, Hadassah Academic College, 37 Hanevi’im Street, Jerusalem
9101001, Israel.
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Yuan Y, Wu CTM. Recent Development of Non-Contact Multi-Target Vital Sign Detection and Location Tracking Based on Metamaterial Leaky Wave Antennas. Sensors (Basel) 2021; 21:3619. [PMID: 34067460 PMCID: PMC8197017 DOI: 10.3390/s21113619] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 05/14/2021] [Accepted: 05/19/2021] [Indexed: 12/02/2022]
Abstract
Microwave radar sensors have been developed for non-contact monitoring of the health condition and location of targets, which will cause minimal discomfort and eliminate sanitation issues, especially in a pandemic situation. To this end, several radar sensor architectures and algorithms have been proposed to detect multiple targets at different locations. Traditionally, beamforming techniques incorporating phase shifters or mechanical rotors are utilized, which is relatively complex and costly. On the other hand, metamaterial (MTM) leaky wave antennas (LWAs) have a unique property of launching waves of different spectral components in different directions. This feature can be utilized to detect multiple targets at different locations to obtain their healthcare and location information accurately, without complex structure and high cost. To this end, this paper reviews the recent development of MTM LWA-based radar sensor architectures for vital sign detection and location tracking. The experimental results demonstrate the effectiveness of MTM vital sign radar compared with different radar sensor architectures.
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Affiliation(s)
| | - Chung-Tse Michael Wu
- Department of Electrical & Computer Engineering, Rutgers University, Piscataway, NJ 08854, USA;
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Kokkoris MD, Kamleitner B. Would You Sacrifice Your Privacy to Protect Public Health? Prosocial Responsibility in a Pandemic Paves the Way for Digital Surveillance. Front Psychol 2020; 11:578618. [PMID: 33071918 PMCID: PMC7531172 DOI: 10.3389/fpsyg.2020.578618] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 08/20/2020] [Indexed: 11/13/2022] Open
Abstract
Digital surveillance methods, such as location tracking apps on smartphones, have been implemented in many countries during the COVID-19 pandemic, but not much is known about predictors of their acceptance. Could it be that prosocial responsibility, to which authorities appealed in order to enhance compliance with quarantine measures, also increases acceptance of digital surveillance and restrictions of privacy? In their fight against the COVID-19 pandemic, governments around the world communicated that self-isolation and social distancing measures are every citizen’s duty in order to protect the health not only of oneself but also of vulnerable others. We suggest that prosocial responsibility besides motivating people to comply with anti-pandemic measures also undermines people’s valuation of privacy. In an online research conducted with US participants, we examined correlates of people’s willingness to sacrifice individual rights and succumb to surveillance with a particular focus on prosocial responsibility. First, replicating prior research, we found that perceived prosocial responsibility was a powerful predictor of compliance with self-isolation and social distancing measures. Second, going beyond prior research, we found that perceived prosocial responsibility also predicted willingness to accept restrictions of individual rights and privacy, as well as to accept digital surveillance for the sake of public health. While we identify a range of additional predictors, the effects of prosocial responsibility hold after controlling for alternative processes, such as perceived self-risk, impact of the pandemic on oneself, or personal value of freedom. These findings suggest that prosocial responsibility may act as a Trojan horse for privacy compromises.
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Affiliation(s)
- Michail D Kokkoris
- Marketing Department, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bernadette Kamleitner
- Marketing Department, Institute for Marketing and Consumer Research, WU Vienna University of Economics and Business, Vienna, Austria
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9
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Wang W, Adamczyk PG. Analyzing Gait in the Real World Using Wearable Movement Sensors and Frequently Repeated Movement Paths. Sensors (Basel) 2019; 19:E1925. [PMID: 31022889 PMCID: PMC6515355 DOI: 10.3390/s19081925] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 04/17/2019] [Accepted: 04/22/2019] [Indexed: 11/22/2022]
Abstract
Assessing interventions for mobility disorders using real-life movement remains an unsolved problem. We propose a new method combining the strengths of traditional laboratory studies where environment is strictly controlled, and field-based studies where subjects behave naturally. We use a foot-mounted inertial sensor, a GPS receiver and a barometric altitude sensor to reconstruct a subject's path and detailed foot movement, both indoors and outdoors, during days-long measurement using strapdown navigation and sensor fusion algorithms. We cluster repeated movement paths based on location, and propose that on these paths, most environmental and behavioral factors (e.g., terrain and motivation) are as repeatable as in a laboratory. During each bout of movement along a frequently repeated path, any synchronized measurement can be isolated for study, enabling focused statistical comparison of different interventions. We conducted a 10-day test on one subject wearing athletic shoes and sandals each for five days. The algorithm detected four frequently-repeated straight walking paths with at least 300 total steps and repetitions on at least three days for each condition. Results on these frequently-repeated paths indicated significantly lower foot clearance and shorter stride length and a trend toward decreased stride width when wearing athletic shoes vs. sandals. Comparisons based on all straight walking were similar, showing greater statistical power, but higher variability in the data. The proposed method offers a new way to evaluate how mobility interventions affect everyday movement behavior.
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Affiliation(s)
- Weixin Wang
- Department of Mechanical Engineering, University of Wisconsin⁻Madison, Madison, WI 53706, USA.
| | - Peter Gabriel Adamczyk
- Department of Mechanical Engineering, University of Wisconsin⁻Madison, Madison, WI 53706, USA.
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10
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Nebeker C, Harlow J, Espinoza Giacinto R, Orozco-Linares R, Bloss CS, Weibel N. Ethical and regulatory challenges of research using pervasive sensing and other emerging technologies: IRB perspectives. AJOB Empir Bioeth 2018; 8:266-276. [PMID: 29125425 DOI: 10.1080/23294515.2017.1403980] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Vast quantities of personal health information and private identifiable information are being created through mobile apps, wearable sensors, and social networks. While new strategies and tools for obtaining health data have expanded researchers' abilities to design and test personalized and adaptive health interventions, the deployment of pervasive sensing and computational techniques to gather research data is raising ethical challenges for Institutional Review Boards (IRBs) charged with protecting research participants. To explore experiences with, and perceptions about, technology-enabled research, and identify solutions for promoting responsible conduct of this research we conducted focus groups with human research protection program and IRB affiliates. Our findings outline the need for increased collaboration across stakeholders in terms of: (1) shared and dynamic resources that improve awareness of technologies and decrease potential threats to participant privacy and data confidentiality, and (2) development of appropriate and dynamic standards through collaboration with stakeholders in the research ethics community.
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Affiliation(s)
- Camille Nebeker
- a Department of Family Medicine and Public Health , School of Medicine, University of California San Diego.,b Center for Wireless and Population Health Systems , Qualcomm Institute, University of California San Diego.,c Moores Cancer Center , University of California San Diego Health
| | - John Harlow
- d Arizona State University Center for Policy Informatics
| | | | | | - Cinnamon S Bloss
- a Department of Family Medicine and Public Health , School of Medicine, University of California San Diego.,b Center for Wireless and Population Health Systems , Qualcomm Institute, University of California San Diego.,f Department of Psychiatry , University of California San Diego
| | - Nadir Weibel
- b Center for Wireless and Population Health Systems , Qualcomm Institute, University of California San Diego.,g Department of Computer Science Engineering , University of California San Diego
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Banos O, Villalonga C, Bang J, Hur T, Kang D, Park S, Huynh-The T, Le-Ba V, Amin MB, Razzaq MA, Khan WA, Hong CS, Lee S. Human Behavior Analysis by Means of Multimodal Context Mining. Sensors (Basel) 2016; 16:s16081264. [PMID: 27517928 PMCID: PMC5017429 DOI: 10.3390/s16081264] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Revised: 07/12/2016] [Accepted: 08/05/2016] [Indexed: 11/24/2022]
Abstract
There is sufficient evidence proving the impact that negative lifestyle choices have on people’s health and wellness. Changing unhealthy behaviours requires raising people’s self-awareness and also providing healthcare experts with a thorough and continuous description of the user’s conduct. Several monitoring techniques have been proposed in the past to track users’ behaviour; however, these approaches are either subjective and prone to misreporting, such as questionnaires, or only focus on a specific component of context, such as activity counters. This work presents an innovative multimodal context mining framework to inspect and infer human behaviour in a more holistic fashion. The proposed approach extends beyond the state-of-the-art, since it not only explores a sole type of context, but also combines diverse levels of context in an integral manner. Namely, low-level contexts, including activities, emotions and locations, are identified from heterogeneous sensory data through machine learning techniques. Low-level contexts are combined using ontological mechanisms to derive a more abstract representation of the user’s context, here referred to as high-level context. An initial implementation of the proposed framework supporting real-time context identification is also presented. The developed system is evaluated for various realistic scenarios making use of a novel multimodal context open dataset and data on-the-go, demonstrating prominent context-aware capabilities at both low and high levels.
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Affiliation(s)
- Oresti Banos
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
- Telemedicine Group, Center for Telematics and Information Technology, University of Twente, Enschede 7500AE, The Netherlands.
| | - Claudia Villalonga
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
- Department of Computer Architecture and Computer Technology, Research Center on Information and Communications Technology, University of Granada, Granada E18071, Spain.
| | - Jaehun Bang
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Taeho Hur
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Donguk Kang
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Sangbeom Park
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Thien Huynh-The
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Vui Le-Ba
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Muhammad Bilal Amin
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Muhammad Asif Razzaq
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Wahajat Ali Khan
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Choong Seon Hong
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
| | - Sungyoung Lee
- Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea.
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Chóliz J, Hernández A, Valdovinos A. A framework for UWB-based communication and location tracking systems for wireless sensor networks. Sensors (Basel) 2011; 11:9045-68. [PMID: 22164120 PMCID: PMC3231499 DOI: 10.3390/s110909045] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2011] [Revised: 09/10/2011] [Accepted: 09/20/2011] [Indexed: 11/16/2022]
Abstract
Ultra wideband (UWB) radio technology is nowadays one of the most promising technologies for medium-short range communications. It has a wide range of applications including wireless sensor networks (WSN) with simultaneous data transmission and location tracking. The combination of location and data transmission is important in order to increase flexibility and reduce the cost and complexity of the system deployment. In this scenario, accuracy is not the only evaluation criteria, but also the amount of resources associated to the location service, as it has an impact not only on the location capacity of the system but also on the sensor data transmission capacity. Although several studies can be found in the literature addressing UWB-based localization, these studies mainly focus on distance estimation and position calculation algorithms. Practical aspects such as the design of the functional architecture, the procedure for the transmission of the associated information between the different elements of the system, and the need of tracking multiple terminals simultaneously in various application scenarios, are generally omitted. This paper provides a complete system level evaluation of a UWB-based communication and location system for Wireless Sensor Networks, including aspects such as UWB-based ranging, tracking algorithms, latency, target mobility and MAC layer design. With this purpose, a custom simulator has been developed, and results with real UWB equipment are presented too.
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Affiliation(s)
- Juan Chóliz
- Research Institute of Engineering in Aragón, I3A, University of Zaragoza, C/María de Luna 3, Zaragoza 50018, Spain.
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