In a 2012 survey, in the United States alone, there were more than 35 000 reported suicides with approximately 1800 of being psychiatric inpatients. Recent Centers for Disease Control and Prevention (CDC) reports indicate an upward trend in these numbers. In psychiatric facilities, staff perform intermittent or continuous observation of patients manually in order to prevent such tragedies, but studies show that they are insufficient, and also consume staff time and resources. In this paper, we present the Watch-Dog system, to address the problem of detecting self-harming activities when attempted by in-patients in clinical settings. Watch-Dog comprises of three key components-Data sensed by tiny accelerometer sensors worn on wrists of subjects; an efficient algorithm to classify whether a user is active versus dormant (i.e., performing a physical activity versus not performing any activity); and a novel decision selection algorithm based on random forests and continuity indices for fine grained activity classification. With data acquired from 11 subjects performing a series of activities (both self-harming and otherwise), Watch-Dog achieves a classification accuracy of , , and for same-user 10-fold cross-validation, cross-user 10-fold cross-validation, and cross-user leave-one-out evaluation, respectively. We believe that the problem addressed in this paper is practical, important, and timely. We also believe that our proposed system is practically deployable, and related discussions are provided in this paper.
To my loving family and friends for their patience and support. I want to give special note of appreciation to my late mother Madhu Panwar for her sacrifice and hard work which she put in to teach me the importance of hardwork and being good human. She always wanted to see me succeed. She sacrificed a lot of her personal interest and ambitions to provide all the necessary resources needed for my success. Mom, this is for you! My twin brother Anupam motivated me to do research and taught me never give up attitude. My father Dr. HR Panwar always supported my decision. My elder brother Anshuman worked as catalyst for my success. Finally, I am forever indebted to my family for their understanding, endless patience and encouragement when it was most required. ACKNOWLEDGMENTS This work has been supported and funded by National Science Foundation (NSF). My sincere gratitude to Dr. Sriram Chellappan for his advice and guidance. He always motivated me to work on the problems that matter and affect society. I owe him a lot for having given directions to my thoughts and unlimited encouragement. Without his insight and patient guidance this work would not have been possible. I am very thankful to Department of Civil, Architectural
No abstract
With the rapid growth of interconnected technologies in the recent time, the world is going under a huge change. Medical and healthcare sectors are also influenced by the advancement in connected technologies. Internet of Things (IoT) in medical device has played a key role in increasing the facilities which can be provided by the healthcare sector. As the healthcare sector is getting digitalized and millions of interconnected devices would communicate important information, it increases the risk factor and new privacy and security issues would arise. This paper focuses on how secure communication between the devices can be achieved and how a weak link in the chain can turn into disaster. It would also look on the research directions which can be done to strengthen the system.
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