Vivek Chandel, A. Sinharay, Nasimuddin Ahmed, Avik Ghose
Inertial Measurement Units (IMUs) embedded in commercial mobile devices are a good choice for continuous monitoring in healthcare domain due to their attractive form factor and low power consumption. We present improved and accurate sensing algorithms using a single IMU to sense basic events like step count, stride length, fall, immobility etc. Our algorithms have been shown to perform better than the state of the art algorithms, and are implemented in such a way that IMU is not bound to any specific position or orientation with respect to the user. We propose a 3-layer based framework for a complete end-to-end system architecture for IoT enabled health monitoring, useful for application in areas like individual fitness monitoring and elderly care.
{"title":"Exploiting IMU Sensors for IOT Enabled Health Monitoring","authors":"Vivek Chandel, A. Sinharay, Nasimuddin Ahmed, Avik Ghose","doi":"10.1145/2933566.2933569","DOIUrl":"https://doi.org/10.1145/2933566.2933569","url":null,"abstract":"Inertial Measurement Units (IMUs) embedded in commercial mobile devices are a good choice for continuous monitoring in healthcare domain due to their attractive form factor and low power consumption. We present improved and accurate sensing algorithms using a single IMU to sense basic events like step count, stride length, fall, immobility etc. Our algorithms have been shown to perform better than the state of the art algorithms, and are implemented in such a way that IMU is not bound to any specific position or orientation with respect to the user. We propose a 3-layer based framework for a complete end-to-end system architecture for IoT enabled health monitoring, useful for application in areas like individual fitness monitoring and elderly care.","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129084473","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}
Today's Healthcare systems are built around an "illness"-driven model where all the stakeholders benefit when people become "ill". There needs to be a paradigm shift to convert this into a "wellness"-driven model. However, in order to create such systems, one needs to build affordable, easily-usable and mass-deployable solutions. We look at three use cases and try to provide solutions -- a) It is seen that a vast majority of the population is affected by "silent-killer" lifestyle diseases like cardiac artery disease (CAD), chronic obstructive pulmonary disease (COPD) and diabetes -- early detection and screening for such diseases are really useful. In this paper, we present how to detect early onset of these using mobile phones and low-cost attachments to mobile phones followed by signal processing and machine learning based analytics b) In rural / semi-urban areas of developing countries, a big problem is early diagnosis of hypertension among pregnant mothers -- it is seen a large number of complications during birth can be avoided if hypertension of pregnant mothers are controlled. In this paper we present how to measure cuff-less blood pressure affordably using just a smart phone and its camera for this. c) Finally, there is a huge number of stroke patients who need rehabilitation therapy -- such treatment typically requires sophisticated rehab-labs in hospitals which is not only costly, but also has accessibility issues. We discuss how a Kinect-sensor based system at home can be used followed by sensor data analytics to help in diagnosis, guidance and compliance to the therapy.
{"title":"Data-driven Healthcare using Affordable Sensing: Screening, Diagnosis and Therapy","authors":"A. Pal","doi":"10.1145/2933566.2936014","DOIUrl":"https://doi.org/10.1145/2933566.2936014","url":null,"abstract":"Today's Healthcare systems are built around an \"illness\"-driven model where all the stakeholders benefit when people become \"ill\". There needs to be a paradigm shift to convert this into a \"wellness\"-driven model. However, in order to create such systems, one needs to build affordable, easily-usable and mass-deployable solutions. We look at three use cases and try to provide solutions -- a) It is seen that a vast majority of the population is affected by \"silent-killer\" lifestyle diseases like cardiac artery disease (CAD), chronic obstructive pulmonary disease (COPD) and diabetes -- early detection and screening for such diseases are really useful. In this paper, we present how to detect early onset of these using mobile phones and low-cost attachments to mobile phones followed by signal processing and machine learning based analytics b) In rural / semi-urban areas of developing countries, a big problem is early diagnosis of hypertension among pregnant mothers -- it is seen a large number of complications during birth can be avoided if hypertension of pregnant mothers are controlled. In this paper we present how to measure cuff-less blood pressure affordably using just a smart phone and its camera for this. c) Finally, there is a huge number of stroke patients who need rehabilitation therapy -- such treatment typically requires sophisticated rehab-labs in hospitals which is not only costly, but also has accessibility issues. We discuss how a Kinect-sensor based system at home can be used followed by sensor data analytics to help in diagnosis, guidance and compliance to the therapy.","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129200894","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 Hwee-Pink","authors":"H. Tan","doi":"10.1145/3254077","DOIUrl":"https://doi.org/10.1145/3254077","url":null,"abstract":"","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116742842","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}
This paper makes the case for combining IoT technologies and persuasive interventions, such as behavioral insights, to bring about healthy behavior change. Approaches like Gamification, Aggregation and Personalization can applied and combined in the IoT context to help change and reinforce desired behaviors. Two examples from the Health Promotion Board (HPB) in Singapore will be shared to illustrate how this can be done, at local and national levels.
{"title":"IoT-Enabled Health Promotion","authors":"Vanessa Tan, Susheela A. Varghese","doi":"10.1145/2933566.2933571","DOIUrl":"https://doi.org/10.1145/2933566.2933571","url":null,"abstract":"This paper makes the case for combining IoT technologies and persuasive interventions, such as behavioral insights, to bring about healthy behavior change. Approaches like Gamification, Aggregation and Personalization can applied and combined in the IoT context to help change and reinforce desired behaviors. Two examples from the Health Promotion Board (HPB) in Singapore will be shared to illustrate how this can be done, at local and national levels.","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121495642","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: Paper Session 2","authors":"S. Eswaran","doi":"10.1145/3254080","DOIUrl":"https://doi.org/10.1145/3254080","url":null,"abstract":"","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124867915","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}
Should people need to be nudged to make healthier lifestyle choices? Critics of the nudge theory believe that using behavioral sciences to influence people's decisions is paternalistic and unnecessary. But on the other hand, we know that people do not always make the most rational choices for themselves, and this comes at a growing burden to society. How can we strike a balance? In this talk, we will look at the health promotion landscape in Singapore, with growing challenges such as obesity and diabetes - set against the backdrop of a workforce that is sometimes too busy to take care of their health, and an ageing population that requires more support. We will examine how the Health Promotion Board of Singapore has taken steps to address the gap between "knowing" and "doing" by shifting its focus from health education to behavior change. Various examples of this approach will be touched on, such as the introduction of innovative health programs, campaigns, partnerships and use of persuasive technology to make it increasingly easier for Singaporeans form and sustain healthier habits. Finally, we will get a glimpse of what living healthily in Singapore may be like in the year 2020.
{"title":"Small Nudges, Big Impact: Innovative Approaches to Health Promotion in Singapore","authors":"Vanessa Tan","doi":"10.1145/2933566.2935685","DOIUrl":"https://doi.org/10.1145/2933566.2935685","url":null,"abstract":"Should people need to be nudged to make healthier lifestyle choices? Critics of the nudge theory believe that using behavioral sciences to influence people's decisions is paternalistic and unnecessary. But on the other hand, we know that people do not always make the most rational choices for themselves, and this comes at a growing burden to society. How can we strike a balance? In this talk, we will look at the health promotion landscape in Singapore, with growing challenges such as obesity and diabetes - set against the backdrop of a workforce that is sometimes too busy to take care of their health, and an ageing population that requires more support. We will examine how the Health Promotion Board of Singapore has taken steps to address the gap between \"knowing\" and \"doing\" by shifting its focus from health education to behavior change. Various examples of this approach will be touched on, such as the introduction of innovative health programs, campaigns, partnerships and use of persuasive technology to make it increasingly easier for Singaporeans form and sustain healthier habits. Finally, we will get a glimpse of what living healthily in Singapore may be like in the year 2020.","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124250902","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: Poster Session","authors":"H. Tan","doi":"10.1145/3254079","DOIUrl":"https://doi.org/10.1145/3254079","url":null,"abstract":"","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134162129","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}
The American Medical Association Family Medical Guide is a comprehensive medical reference book for non-medical professionals. The book uses a series of flow charts to help users diagnose their symptoms by answering yes and no questions. The idea presented in this paper is to leverage the information in the book to make a chat bot for a mobile phone user. We develop a tool for crowd workers to train the chat bot using the information in the book. We present a framework for the crowd worker. Information is classified as symptom, diagnosis, or care. The chat bot makes the information accessible to people that primarily use a mobile phone and are not medical professionals. By having the data on the phone, we are able to make the data actionable by integrating it with the computational capabilities and sensors of the phone.
{"title":"From Books to Bots: Using Medical Literature to Create a Chat Bot","authors":"Michael H. Fischer, M. Lam","doi":"10.1145/2933566.2933573","DOIUrl":"https://doi.org/10.1145/2933566.2933573","url":null,"abstract":"The American Medical Association Family Medical Guide is a comprehensive medical reference book for non-medical professionals. The book uses a series of flow charts to help users diagnose their symptoms by answering yes and no questions. The idea presented in this paper is to leverage the information in the book to make a chat bot for a mobile phone user. We develop a tool for crowd workers to train the chat bot using the information in the book. We present a framework for the crowd worker. Information is classified as symptom, diagnosis, or care. The chat bot makes the information accessible to people that primarily use a mobile phone and are not medical professionals. By having the data on the phone, we are able to make the data actionable by integrating it with the computational capabilities and sensors of the phone.","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122870727","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}
Chetanya Puri, A. Ukil, S. Bandyopadhyay, Rituraj Singh, A. Pal, K. Mandana
Ubiquity of smartphones with array of inbuilt sensors, pave ways to inexpensive mobile-health systems, particularly for cardio-vascular health monitoring. Smartphones, wearable sensors, and body area sensors play an important role as a part of Internet of Things (IoT) m-health ecosystem. In this paper, we present iCarMa to enable an inexpensive auto-triggered arrhythmia cardiac management solution catering the need of in-house, round-the-clock cardiac health monitoring. It facilitates early detection of fatal cardiac conditions like asystole, extreme bradycardia, extreme tachycardia, ventricular flutter and ventricular tachycardia, which often compel an individual to get admitted in Intensive Care Unit (ICU). Smartphone or wearable sensor extracted photoplethysmogram (PPG) is the sole physiological signal that is considered to characterize the cardiac anomalous events. Our main novelty is to precisely detect and remove the motion artifacts in PPG signals and to ensure accuracy in arrhythmia condition detection, specifically to reduce the false negative alarms. We establish the efficacy of proposed solution, iCarMa by large set of experiments with field-collected and MIT-Physionet PPG signals.
{"title":"iCarMa: Inexpensive Cardiac Arrhythmia Management -- An IoT Healthcare Analytics Solution","authors":"Chetanya Puri, A. Ukil, S. Bandyopadhyay, Rituraj Singh, A. Pal, K. Mandana","doi":"10.1145/2933566.2933567","DOIUrl":"https://doi.org/10.1145/2933566.2933567","url":null,"abstract":"Ubiquity of smartphones with array of inbuilt sensors, pave ways to inexpensive mobile-health systems, particularly for cardio-vascular health monitoring. Smartphones, wearable sensors, and body area sensors play an important role as a part of Internet of Things (IoT) m-health ecosystem. In this paper, we present iCarMa to enable an inexpensive auto-triggered arrhythmia cardiac management solution catering the need of in-house, round-the-clock cardiac health monitoring. It facilitates early detection of fatal cardiac conditions like asystole, extreme bradycardia, extreme tachycardia, ventricular flutter and ventricular tachycardia, which often compel an individual to get admitted in Intensive Care Unit (ICU). Smartphone or wearable sensor extracted photoplethysmogram (PPG) is the sole physiological signal that is considered to characterize the cardiac anomalous events. Our main novelty is to precisely detect and remove the motion artifacts in PPG signals and to ensure accuracy in arrhythmia condition detection, specifically to reduce the false negative alarms. We establish the efficacy of proposed solution, iCarMa by large set of experiments with field-collected and MIT-Physionet PPG signals.","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115916073","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}
SleepSensei is an automated sleep quality monitor and estimates the sleep duration for a user. It essentially builds a personalized model for determining the apt sleep duration for a given user. In our model, with the help of multiple inter-connected devices, we combine features related to user surroundings and those related to user movements during sleep. We use regression models in our system to calculate "sleep share" of a user, and report an MSE as low as 0.0041 when tested on 7 users, with more than a week's data. We also develop a smart alarm based on the notion of "sleep quota" from the model. The alarm has an average precision of 0.87 from the survey conducted. We also present an in-depth feature analysis to give further insights of individual sleep behavior.
{"title":"SleepSensei: An Automated Sleep Quality Monitor and Sleep Duration Estimator","authors":"Amrith Krishna, Madhumita Mallick, Bivas Mitra","doi":"10.1145/2933566.2933570","DOIUrl":"https://doi.org/10.1145/2933566.2933570","url":null,"abstract":"SleepSensei is an automated sleep quality monitor and estimates the sleep duration for a user. It essentially builds a personalized model for determining the apt sleep duration for a given user. In our model, with the help of multiple inter-connected devices, we combine features related to user surroundings and those related to user movements during sleep. We use regression models in our system to calculate \"sleep share\" of a user, and report an MSE as low as 0.0041 when tested on 7 users, with more than a week's data. We also develop a smart alarm based on the notion of \"sleep quota\" from the model. The alarm has an average precision of 0.87 from the survey conducted. We also present an in-depth feature analysis to give further insights of individual sleep behavior.","PeriodicalId":292301,"journal":{"name":"Proceedings of the First Workshop on IoT-enabled Healthcare and Wellness Technologies and Systems","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133913903","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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