Tremor Detection Using Smartphone-based Acoustic Sensing Wei Wang Xun Wang Abstract State Key Laboratory for Novel State Key Laboratory for Novel In this demo,we present a tremor detection application on Software Technology,Nanjing Software Technology,Nanjing smartphones for early diagnosis of Parkinson's disease. University University Our tremor detection scheme uses inaudible sound emit- Nanjing,210023,china Nanjing,210023,china ted by the built-in speaker on the smartphone.We measure ww@nju.edu.cn 131220134@smail.nju.edu.cn the movement of the hand by extracting the phase of sound waves reflected by the hand.Our application can classify whether the hand is static,moving,or trembling,without re- quiring the patient to hold the phone.The application can Lei Xie also determine the intensity of the tremor by measuring pa- State Key Laboratory for Novel rameters such as the trembling frequency and the trembling Software Technology,Nanjing magnitude. University Nanjing,210023,china Author Keywords Ixie@nju.edu.cn Ultrasound;Tremor Detection;Smartphone;Device-free ACM Classification Keywords H.5.m [Information interfaces and presentation (e.g.,HCI)]: Miscellaneous Paste the appropriate copyright statement here.ACM now supports three ditferent copyright statements: Introduction .ACM copyight:ACM holds the copyright on the work.This is the historical approach. Tremor is an important symptom associated with disorders License:The author(s)retain copyright,but ACM recelves an exclusive such as Parkinson's Disease(PD)or Alzheimer's disease publication license. (AD).Tremor detection and classification are important for Open Access:The author(s)wish to pay for the work to be open access.The additlonal fee must be paid to ACM early diagnosis of these disorders.Therefore,it is important This text field is large enough to hold the appropriate release statement assuming it is single spaced in a sans-serif 7 point tont. to develop a convenient way to monitor and record tremor Every submission will be assigned their own unique DOI string to be included here. behaviors that can be used by anyone at any place.Tremor Detection Using Smartphone-based Acoustic Sensing Wei Wang State Key Laboratory for Novel Software Technology, Nanjing University Nanjing, 210023, china ww@nju.edu.cn Xun Wang State Key Laboratory for Novel Software Technology, Nanjing University Nanjing, 210023, china 131220134@smail.nju.edu.cn Lei Xie State Key Laboratory for Novel Software Technology, Nanjing University Nanjing, 210023, china lxie@nju.edu.cn Paste the appropriate copyright statement here. ACM now supports three different copyright statements: • ACM copyright: ACM holds the copyright on the work. This is the historical approach. • License: The author(s) retain copyright, but ACM receives an exclusive publication license. • Open Access: The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is single spaced in a sans-serif 7 point font. Every submission will be assigned their own unique DOI string to be included here. Abstract In this demo, we present a tremor detection application on smartphones for early diagnosis of Parkinson’s disease. Our tremor detection scheme uses inaudible sound emit￾ted by the built-in speaker on the smartphone. We measure the movement of the hand by extracting the phase of sound waves reflected by the hand. Our application can classify whether the hand is static, moving, or trembling, without re￾quiring the patient to hold the phone. The application can also determine the intensity of the tremor by measuring pa￾rameters such as the trembling frequency and the trembling magnitude. Author Keywords Ultrasound; Tremor Detection; Smartphone; Device-free ACM Classification Keywords H.5.m [Information interfaces and presentation (e.g., HCI)]: Miscellaneous Introduction Tremor is an important symptom associated with disorders such as Parkinson’s Disease (PD) or Alzheimer’s disease (AD). Tremor detection and classification are important for early diagnosis of these disorders. Therefore, it is important to develop a convenient way to monitor and record tremor behaviors that can be used by anyone at any place