DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)最新文献
Yu Huang, Jiaqi Gong, Mark Rucker, Philip I. Chow, Karl C. Fua, M. Gerber, B. Teachman, Laura E. Barnes
Better understanding of an individual's smartphone use can help researchers to understand the relationship between behaviors and mental health, and ultimately improve methods for early detection, evaluation, and intervention. This relationship may be particularly significant for individuals with social anxiety, for whom stress from social interactions may arise repeatedly and unexpectedly over the course of a day. For this reason, we present an exploratory study of behavioral markers extracted from smartphone data. We examine fine-grained behaviors before and after smartphone communication events across social anxiety levels. To discover behavioral markers, we model the smartphone as a linear dynamical system with the accelerometer data as output. In a two-week study of 52 college students, we find substantially different behavioral markers prior to outgoing phone calls when comparing individuals with high and low social anxiety.
{"title":"Discovery of Behavioral Markers of Social Anxiety from Smartphone Sensor Data","authors":"Yu Huang, Jiaqi Gong, Mark Rucker, Philip I. Chow, Karl C. Fua, M. Gerber, B. Teachman, Laura E. Barnes","doi":"10.1145/3089341.3089343","DOIUrl":"https://doi.org/10.1145/3089341.3089343","url":null,"abstract":"Better understanding of an individual's smartphone use can help researchers to understand the relationship between behaviors and mental health, and ultimately improve methods for early detection, evaluation, and intervention. This relationship may be particularly significant for individuals with social anxiety, for whom stress from social interactions may arise repeatedly and unexpectedly over the course of a day. For this reason, we present an exploratory study of behavioral markers extracted from smartphone data. We examine fine-grained behaviors before and after smartphone communication events across social anxiety levels. To discover behavioral markers, we model the smartphone as a linear dynamical system with the accelerometer data as output. In a two-week study of 52 college students, we find substantially different behavioral markers prior to outgoing phone calls when comparing individuals with high and low social anxiety.","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85524960","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":"Session details: Digital Biomarkers for Behavioral and Cognitive Health Session","authors":"D. Estrin","doi":"10.1145/3257958","DOIUrl":"https://doi.org/10.1145/3257958","url":null,"abstract":"","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73264440","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}
It is our great pleasure to welcome you to the ACM 1st workshop on Digital Biomarkers 2017 (DigitalBioMarkers'17). The workshop will bring academics, industry researchers and medical researchers together to address the modeling, testing, and validation of new digital biomarkers for evaluating and predicting onset of diseases/health conditions, response to treatments, and effects of interventions. The workshop aims to facilitate a systematic discussion among experts from different knowledge domains including mobile sensing, systems, machine learning, medicine and health sciences in order to (i) identify new digital biomarkers relevant to behavioral, chronic, and degenerative conditions, (ii) identify the key shortcomings of the existing mobile and wearable sensor systems, and research platforms (e.g., ResearchKit(™) and ResearchStack) for digital biomarker inference in terms of scalability, customizability, and sensing affordances, (iii) find realistic solutions towards building new digital biomarker evidence engine leveraging sensor data from a variety of mobile systems (e.g., smartphones, wearables, IoT devices, and other relevant digital traces), (iv) identify key data collection, labeling, testing and validation methodologies for development of digital biomarkers. The call for papers attracted highly relevant submissions from around the world. The program committee accepted 6 short papers out of 9 submissions. In addition to the presentations of the 6 accepted papers, the workshop will feature one a morning keynote and an afternoon panel session. Keynote: "A Quantum of Solace: Digital Traces and Mental Health", Prof. Vincent M. B. Silenzio, University of Rochester School of Medicine & Dentistry Designing studies for feasibility testing, refinement and validation of digital biomarkers Panel Session
我们非常高兴地欢迎您参加ACM 2017年第一届数字生物标志物研讨会(DigitalBioMarkers'17)。研讨会将汇集学者、行业研究人员和医学研究人员，讨论新的数字生物标志物的建模、测试和验证，以评估和预测疾病/健康状况的发病、对治疗的反应和干预措施的效果。研讨会旨在促进来自不同知识领域的专家之间的系统讨论，包括移动传感，系统，机器学习，医学和健康科学，以便(i)确定与行为，慢性和退行性疾病相关的新数字生物标志物，(ii)确定现有移动和可穿戴传感器系统的主要缺点，以及研究平台(例如，ResearchKit(™)和ResearchStack)在可扩展性，可定制性和传感能力方面用于数字生物标志物推断，(iii)找到利用来自各种移动系统(例如智能手机，可穿戴设备，物联网设备和其他相关数字痕迹)的传感器数据构建新的数字生物标志物证据引擎的现实解决方案，(iv)确定数字生物标志物开发的关键数据收集，标记，测试和验证方法。论文征集活动吸引了来自世界各地的高度相关的论文。计划委员会从9篇提交的论文中接受了6篇短文。除了6篇论文的演讲外，研讨会还将举办上午的主题演讲和下午的小组讨论。主题演讲:“A Quantum of Solace: Digital Traces and Mental Health”，Vincent M. B. Silenzio教授，罗切斯特大学医学与牙科学院，数字生物标志物可行性测试、改进和验证的设计研究小组会议
{"title":"Proceedings of the 1st Workshop on Digital Biomarkers","authors":"D. Estrin, J. P. Pollak, Tauhidur Rahman","doi":"10.1145/3089341","DOIUrl":"https://doi.org/10.1145/3089341","url":null,"abstract":"It is our great pleasure to welcome you to the ACM 1st workshop on Digital Biomarkers 2017 (DigitalBioMarkers'17). The workshop will bring academics, industry researchers and medical researchers together to address the modeling, testing, and validation of new digital biomarkers for evaluating and predicting onset of diseases/health conditions, response to treatments, and effects of interventions. The workshop aims to facilitate a systematic discussion among experts from different knowledge domains including mobile sensing, systems, machine learning, medicine and health sciences in order to (i) identify new digital biomarkers relevant to behavioral, chronic, and degenerative conditions, (ii) identify the key shortcomings of the existing mobile and wearable sensor systems, and research platforms (e.g., ResearchKit(™) and ResearchStack) for digital biomarker inference in terms of scalability, customizability, and sensing affordances, (iii) find realistic solutions towards building new digital biomarker evidence engine leveraging sensor data from a variety of mobile systems (e.g., smartphones, wearables, IoT devices, and other relevant digital traces), (iv) identify key data collection, labeling, testing and validation methodologies for development of digital biomarkers. \u0000 \u0000The call for papers attracted highly relevant submissions from around the world. The program committee accepted 6 short papers out of 9 submissions. In addition to the presentations of the 6 accepted papers, the workshop will feature one a morning keynote and an afternoon panel session. \u0000Keynote: \"A Quantum of Solace: Digital Traces and Mental Health\", Prof. Vincent M. B. Silenzio, University of Rochester School of Medicine & Dentistry \u0000Designing studies for feasibility testing, refinement and validation of digital biomarkers Panel Session","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"247 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74895031","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}
Bo-Jhang Ho, Renju Liu, Hsiao-Yun Tseng, M. Srivastava
Muscular dystrophy is a group of genetic diseases that cause the loss of muscles and hence weakening the muscle strength. A typical treatment for muscular dystrophy patients is routinely performing weight exercise to slow down the loss in muscles. Thus, we propose a system MyoBuddy to help both physical therapists and patients to keep track of the weights in workout activities based on electromyography (EMG) sensors embedded in Myo armband. In our study, we collect 102 sessions of EMG data from barbell bicep curl exercise with a range of weights from 20 to 70 lbs with a 10-pound increment. Both Support Vector Machine and Random Forest algorithms are explored to classify which weight of barbells are lifted. At the end, we achieve 77.1% classification accuracy on average.
{"title":"MyoBuddy: Detecting Barbell Weight Using Electromyogram Sensors","authors":"Bo-Jhang Ho, Renju Liu, Hsiao-Yun Tseng, M. Srivastava","doi":"10.1145/3089341.3089346","DOIUrl":"https://doi.org/10.1145/3089341.3089346","url":null,"abstract":"Muscular dystrophy is a group of genetic diseases that cause the loss of muscles and hence weakening the muscle strength. A typical treatment for muscular dystrophy patients is routinely performing weight exercise to slow down the loss in muscles. Thus, we propose a system MyoBuddy to help both physical therapists and patients to keep track of the weights in workout activities based on electromyography (EMG) sensors embedded in Myo armband. In our study, we collect 102 sessions of EMG data from barbell bicep curl exercise with a range of weights from 20 to 70 lbs with a 10-pound increment. Both Support Vector Machine and Random Forest algorithms are explored to classify which weight of barbells are lifted. At the end, we achieve 77.1% classification accuracy on average.","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80116977","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}
Mobile sensing technologies and machine learning techniques have been successfully exploited to build effective systems for mental health monitoring and intervention. Various approaches have recently been proposed to effectively exploit contextual information such as mobility, communication and mobile usage patterns for quantifying users' emotional states and wellbeing. In particular, it has been shown that location information collected by means of smartphones can be successfully used to monitor and predict depression levels, as measured by means of standard scores such as PHQ-8. In this paper, we investigate the design of novel digital biomarkers based on the fine-grained characterization of the mobility patterns of a user, also considering the temporal dimension of their movements (e.g., sequence of places visited by them). We show that the proposed biomarkers have a statistically significant association with emotional states. We also demonstrate that emotional states have a stronger relationship with mobility patterns of weekdays compared to all days of a week. Finally, we discuss the challenges in using these biomarkers in the implementation of "emotion-aware" systems for digital health.
{"title":"Designing Effective Movement Digital Biomarkers for Unobtrusive Emotional State Mobile Monitoring","authors":"Abhinav Mehrotra, Mirco Musolesi","doi":"10.1145/3089341.3089342","DOIUrl":"https://doi.org/10.1145/3089341.3089342","url":null,"abstract":"Mobile sensing technologies and machine learning techniques have been successfully exploited to build effective systems for mental health monitoring and intervention. Various approaches have recently been proposed to effectively exploit contextual information such as mobility, communication and mobile usage patterns for quantifying users' emotional states and wellbeing. In particular, it has been shown that location information collected by means of smartphones can be successfully used to monitor and predict depression levels, as measured by means of standard scores such as PHQ-8. In this paper, we investigate the design of novel digital biomarkers based on the fine-grained characterization of the mobility patterns of a user, also considering the temporal dimension of their movements (e.g., sequence of places visited by them). We show that the proposed biomarkers have a statistically significant association with emotional states. We also demonstrate that emotional states have a stronger relationship with mobility patterns of weekdays compared to all days of a week. Finally, we discuss the challenges in using these biomarkers in the implementation of \"emotion-aware\" systems for digital health.","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"80 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74496416","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":"Session details: Methodology","authors":"J. Pollak","doi":"10.1145/3257960","DOIUrl":"https://doi.org/10.1145/3257960","url":null,"abstract":"","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"109 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74570191","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}
Ridwan Alam, Jiaqi Gong, M. Hanson, Azziza Bankole, M. Anderson, T. Smith-Jackson, J. Lach
Agitation in dementia poses a major health risk for both the patients and their caregivers and induces a huge caregiving burden. Early detection of agitation can facilitate timely intervention and prevent escalation of critical episodes. Sensing behavioral patterns for detecting health critical events is a challenging task. Wearable sensors are often employed for sensing physiological signals, but extracting possible biomarkers for confident detection of early agitation is still an open research. In this paper, we employ an ongoing iterative study to explore the motion biomarkers related to agitation in community-dwelling persons with dementia (PWD). This study uses accelerometers in smart watches to capture PWD behavioral patterns unobtrusively. Analysis of the feature space is performed using data from multiple subjects to discriminate among epochs of onset, preset, and offset of agitation while considering inter-person variability in real deployments. This paper shows the prospect of feature space analysis of the motion data for developing early agitation detection models to deploy in the wild.
{"title":"Motion Biomarkers for Early Detection of Dementia-Related Agitation","authors":"Ridwan Alam, Jiaqi Gong, M. Hanson, Azziza Bankole, M. Anderson, T. Smith-Jackson, J. Lach","doi":"10.1145/3089341.3089344","DOIUrl":"https://doi.org/10.1145/3089341.3089344","url":null,"abstract":"Agitation in dementia poses a major health risk for both the patients and their caregivers and induces a huge caregiving burden. Early detection of agitation can facilitate timely intervention and prevent escalation of critical episodes. Sensing behavioral patterns for detecting health critical events is a challenging task. Wearable sensors are often employed for sensing physiological signals, but extracting possible biomarkers for confident detection of early agitation is still an open research. In this paper, we employ an ongoing iterative study to explore the motion biomarkers related to agitation in community-dwelling persons with dementia (PWD). This study uses accelerometers in smart watches to capture PWD behavioral patterns unobtrusively. Analysis of the feature space is performed using data from multiple subjects to discriminate among epochs of onset, preset, and offset of agitation while considering inter-person variability in real deployments. This paper shows the prospect of feature space analysis of the motion data for developing early agitation detection models to deploy in the wild.","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88906024","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":"Session details: Keynote Address","authors":"D. Estrin","doi":"10.1145/3257957","DOIUrl":"https://doi.org/10.1145/3257957","url":null,"abstract":"","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84192836","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":"Session details: Panel","authors":"J. Pollak","doi":"10.1145/3257961","DOIUrl":"https://doi.org/10.1145/3257961","url":null,"abstract":"","PeriodicalId":92197,"journal":{"name":"DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88434174","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}
DigitalBiomarkers'17 : proceedings of the 1st Workshop on Digital Biomarkers : June 23, 2017, Niagara Falls, NY, USA. Workshop on Digital Biomarkers (1st : 2017 : Niagara Falls, N.Y.)
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