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Enabling Smart Health Applications via Active Acoustic Sensing on Commodity Mobile Devices.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Enabling Smart Health Applications via Active Acoustic Sensing on Commodity Mobile Devices./
作者:
Song, Xingzhe.
面頁冊數:
1 online resource (107 pages)
附註:
Source: Dissertations Abstracts International, Volume: 84-06, Section: B.
Contained By:
Dissertations Abstracts International84-06B.
標題:
Biomarkers. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30163834click for full text (PQDT)
ISBN:
9798358403109
Enabling Smart Health Applications via Active Acoustic Sensing on Commodity Mobile Devices.
Song, Xingzhe.
Enabling Smart Health Applications via Active Acoustic Sensing on Commodity Mobile Devices.
- 1 online resource (107 pages)
Source: Dissertations Abstracts International, Volume: 84-06, Section: B.
Thesis (Ph.D.)--University of Pittsburgh, 2022.
Includes bibliographical references
Past decades have witnessed the development and prosperity of mobile and wearable devices with their merits of portability, energy efficiency, and computational capability. Among applications implemented on these devices, smart health is an emerging field that deploys mobile applications to monitor vital signals, manage healthcare records and conduct disease diagnoses. However, existing techniques are limited to measuring health metrics with evident biomarkers such as induced sound or visual change unless dedicated medical sensors are attached. To improve the practicality and feasibility of smart health applications, this thesis aims to utilize active acoustic sensing on subtle biomarkers that are not audible or observable.This thesis has three major aspects of establishing the active acoustic sensing framework using speaker-microphone pair that are widely available on mobile devices. First, a new system design is proposed to support complete, accurate yet reliable spirometry tests in regular home settings. To achieve this, it measures the chest wall motion based on the sonar system and interprets such motion into lung function indices. Secondly, when the biomarker cannot be intuitively captured as object motion, a channel estimation approach is adopted to quantify muscle tremor induced by muscle fatigue. Lastly, with additional sensing attachments and physiological correlation, active acoustic sensing functionality is further broadened to facial expressions recognition, an intrinsic indicator of mental well-being.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798358403109Subjects--Topical Terms:
2205735
Biomarkers.
Index Terms--Genre/Form:
542853
Electronic books.
Enabling Smart Health Applications via Active Acoustic Sensing on Commodity Mobile Devices.
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Enabling Smart Health Applications via Active Acoustic Sensing on Commodity Mobile Devices.
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Past decades have witnessed the development and prosperity of mobile and wearable devices with their merits of portability, energy efficiency, and computational capability. Among applications implemented on these devices, smart health is an emerging field that deploys mobile applications to monitor vital signals, manage healthcare records and conduct disease diagnoses. However, existing techniques are limited to measuring health metrics with evident biomarkers such as induced sound or visual change unless dedicated medical sensors are attached. To improve the practicality and feasibility of smart health applications, this thesis aims to utilize active acoustic sensing on subtle biomarkers that are not audible or observable.This thesis has three major aspects of establishing the active acoustic sensing framework using speaker-microphone pair that are widely available on mobile devices. First, a new system design is proposed to support complete, accurate yet reliable spirometry tests in regular home settings. To achieve this, it measures the chest wall motion based on the sonar system and interprets such motion into lung function indices. Secondly, when the biomarker cannot be intuitively captured as object motion, a channel estimation approach is adopted to quantify muscle tremor induced by muscle fatigue. Lastly, with additional sensing attachments and physiological correlation, active acoustic sensing functionality is further broadened to facial expressions recognition, an intrinsic indicator of mental well-being.
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