International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare最新文献

Your Day in Your Pocket: Complex Activity Recognition from Smartphone Accelerometers 你的一天在你的口袋:复杂的活动识别从智能手机加速度计

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2023-01-17 DOI: 10.48550/arXiv.2301.06993

Emma Bouton--Bessac, L. Meegahapola, D. Gática-Pérez

{"title":"Your Day in Your Pocket: Complex Activity Recognition from Smartphone Accelerometers","authors":"Emma Bouton--Bessac, L. Meegahapola, D. Gática-Pérez","doi":"10.48550/arXiv.2301.06993","DOIUrl":"https://doi.org/10.48550/arXiv.2301.06993","url":null,"abstract":"Human Activity Recognition (HAR) enables context-aware user experiences where mobile apps can alter content and interactions depending on user activities. Hence, smartphones have become valuable for HAR as they allow large, and diversified data collection. Although previous work in HAR managed to detect simple activities (i.e., sitting, walking, running) with good accuracy using inertial sensors (i.e., accelerometer), the recognition of complex daily activities remains an open problem, specially in remote work/study settings when people are more sedentary. Moreover, understanding the everyday activities of a person can support the creation of applications that aim to support their well-being. This paper investigates the recognition of complex activities exclusively using smartphone accelerometer data. We used a large smartphone sensing dataset collected from over 600 users in five countries during the pandemic and showed that deep learning-based, binary classification of eight complex activities (sleeping, eating, watching videos, online communication, attending a lecture, sports, shopping, studying) can be achieved with AUROC scores up to 0.76 with partially personalized models. This shows encouraging signs toward assessing complex activities only using phone accelerometer data in the post-pandemic world.","PeriodicalId":87275,"journal":{"name":"International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87770671","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}

引用次数: 2

Pervasive Computing Technologies for Healthcare: 16th EAI International Conference, PervasiveHealth 2022, Thessaloniki, Greece, December 12-14, 2022, Proceedings 医疗保健的普适计算技术:第16届EAI国际会议，普适健康2022，塞萨洛尼基，希腊，12月12-14日，2022，会议记录

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-34586-9

引用次数: 0

Exploring Unique App Signature of the Depressed and Non-depressed Through Their Fingerprints on Apps 通过应用程序上的指纹探索抑郁症患者和非抑郁症患者的独特应用签名

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2022-01-31 DOI: 10.31234/osf.io/6mbua

M. Ahmed, Nova Ahmed

{"title":"Exploring Unique App Signature of the Depressed and Non-depressed Through Their Fingerprints on Apps","authors":"M. Ahmed, Nova Ahmed","doi":"10.31234/osf.io/6mbua","DOIUrl":"https://doi.org/10.31234/osf.io/6mbua","url":null,"abstract":"Growing research on re-identification through app usage behavior reveals the privacy threat in having smartphone usage data to third parties. However, re-identifiability of a vulnerable group like the depressed is unexplored. We fill this knowledge gap through an in the wild study on 100 students’ PHQ-9 scale’s data and 7 days’ logged app usage data. We quantify the uniqueness and re-identifiability through exploration of minimum hamming distance in terms of the set of used apps. Our findings show that using app usage data, each of the depressed and non-depressed students is re-identifiable. In fact, using only 7 hours’ data of a week, on average, 91% of the depressed and 88% of the non-depressed are re-identifiable. Moreover, data of a single app category (i.e., Tools) can also be used to re-identify each depressed student. Furthermore, we find that the rate of uniqueness among the depressed students is significantly higher in some app categories. For instance, in the Social Media category, the rate of uniqueness is 9% higher (P=.02, Cohen's d=1.31) and in the Health & Fitness category, this rate is 8% higher (P=.005, Cohen’s d=1.47) than the non-depressed group. Our findings suggest that each of the depressed students has a unique app signature which makes them re-identifiable. Therefore, during the design of the privacy protecting systems, designers need to consider the uniqueness of them to ensure better privacy for this vulnerable group.","PeriodicalId":87275,"journal":{"name":"International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85562614","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}

引用次数: 2

Smartphone-Based Strategy for Quality-of-Life Monitoring in Head and Neck Cancer Survivors 基于智能手机的头颈癌幸存者生活质量监测策略

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-34586-9_12

Laura Lopez-Perez, Itziar Alonso, D. Filippidis, F. Mercalli, S. Cavalieri, E. Martinelli, L. Licitra, Anastassios Manos, M. Cabrera-Umpiérrez, G. Fico

引用次数: 0

Multiclass Semantic Segmentation of Mediterranean Food Images 地中海食物图像的多类语义分割

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-34586-9_4

Fotios S. Konstantakopoulos, Eleni I. Georga, D. Fotiadis

引用次数: 0

Pervasive Computing Technologies for Healthcare: 15th EAI International Conference, Pervasive Health 2021, Virtual Event, December 6-8, 2021, Proceedings 医疗保健的普适计算技术:第15届EAI国际会议，普适健康2021，虚拟事件，2021年12月6日至8日，会议录

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2022-01-01 DOI: 10.1007/978-3-030-99194-4

引用次数: 0

BONVITA: Enabling Integrated Self-Care for Improving Chronic Patient's Wellbeing BONVITA:实现综合自我护理，改善慢性患者的健康

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-34586-9_22

H. Kondylakis, A. Kouroubali, Dimitrios G. Katehakis

引用次数: 0

Healthcare Based on IoT Using Arduino, MPU6050 Accelerometer and Gyroscope Sensor and FSR-174 Strain Gauge for Fatigue 基于物联网的医疗保健，使用Arduino, MPU6050加速度计和陀螺仪传感器以及FSR-174疲劳应变仪

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-34586-9_11

Sara Fernández-Canosa, Verónica López-González, Antonio Consoli, V. Soto-León

引用次数: 0

Less is More: Leveraging Digital Behavioral Markers for Real-Time Identification of Loneliness in Resource-Limited Settings 少即是多:利用数字行为标记在资源有限的环境中实时识别孤独感

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-34586-9_31

M. Ahmed, Nova Ahmed

引用次数: 1

Toward Understanding Users' Interactions with a Mental Health App: An Association Rule Mining Approach 了解用户与心理健康应用程序的交互:一种关联规则挖掘方法

International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-34586-9_32

Ala'a N. Alslaity, Gerry Chan, Richard Wilson, Rita Orji

引用次数: 0