From Systemic to Regional: Personal Health and Medical Monitoring Systems that Adapt to Individual Variance
Doctors require biometric sensor data to improve diagnostic accuracy, monitor a patient’s recovery progress, and make informed decisions about further treatment. Advances in electronics and sensing technologies have led to the development of remote monitoring devices, such as for ECG and blood press...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/156551 https://orcid.org/0000-0001-6166-6138 |
| _version_ | 1811079426606104576 |
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| author | Zhu, Junyi |
| author2 | Mueller, Stefanie |
| author_facet | Mueller, Stefanie Zhu, Junyi |
| author_sort | Zhu, Junyi |
| collection | MIT |
| description | Doctors require biometric sensor data to improve diagnostic accuracy, monitor a patient’s recovery progress, and make informed decisions about further treatment. Advances in electronics and sensing technologies have led to the development of remote monitoring devices, such as for ECG and blood pressure, which can collect biometric data outside of the clinic. However, these forms of systemic biometric signal monitoring only capture limited aspects of one's overall health, lacking detailed information on specific local body regions. In addition, individual patient health conditions are diverse and often complex. Thus, traditional sensing techniques, while effective for the broader population, often do not meet the unique needs of specific patient groups, especially for environments beyond clinic and home.
In this thesis, I will be presenting my Ph.D. work around personalized health and medical monitoring systems that adapt to individual variance, including muscle engagement monitoring during unsupervised rehabilitation, upper airway obstruction monitoring for obstructive sleep apnea, as well as device and measurement setup customization based on the patient’s regional body physique and use environment. |
| first_indexed | 2024-09-23T11:14:50Z |
| format | Thesis |
| id | mit-1721.1/156551 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:14:50Z |
| publishDate | 2024 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1565512024-09-04T03:40:39Z From Systemic to Regional: Personal Health and Medical Monitoring Systems that Adapt to Individual Variance Zhu, Junyi Mueller, Stefanie Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Doctors require biometric sensor data to improve diagnostic accuracy, monitor a patient’s recovery progress, and make informed decisions about further treatment. Advances in electronics and sensing technologies have led to the development of remote monitoring devices, such as for ECG and blood pressure, which can collect biometric data outside of the clinic. However, these forms of systemic biometric signal monitoring only capture limited aspects of one's overall health, lacking detailed information on specific local body regions. In addition, individual patient health conditions are diverse and often complex. Thus, traditional sensing techniques, while effective for the broader population, often do not meet the unique needs of specific patient groups, especially for environments beyond clinic and home. In this thesis, I will be presenting my Ph.D. work around personalized health and medical monitoring systems that adapt to individual variance, including muscle engagement monitoring during unsupervised rehabilitation, upper airway obstruction monitoring for obstructive sleep apnea, as well as device and measurement setup customization based on the patient’s regional body physique and use environment. Ph.D. 2024-09-03T21:06:49Z 2024-09-03T21:06:49Z 2024-05 2024-07-10T13:02:29.760Z Thesis https://hdl.handle.net/1721.1/156551 https://orcid.org/0000-0001-6166-6138 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Zhu, Junyi From Systemic to Regional: Personal Health and Medical Monitoring Systems that Adapt to Individual Variance |
| title | From Systemic to Regional: Personal Health and Medical Monitoring Systems that Adapt to Individual Variance |
| title_full | From Systemic to Regional: Personal Health and Medical Monitoring Systems that Adapt to Individual Variance |
| title_fullStr | From Systemic to Regional: Personal Health and Medical Monitoring Systems that Adapt to Individual Variance |
| title_full_unstemmed | From Systemic to Regional: Personal Health and Medical Monitoring Systems that Adapt to Individual Variance |
| title_short | From Systemic to Regional: Personal Health and Medical Monitoring Systems that Adapt to Individual Variance |
| title_sort | from systemic to regional personal health and medical monitoring systems that adapt to individual variance |
| url | https://hdl.handle.net/1721.1/156551 https://orcid.org/0000-0001-6166-6138 |
| work_keys_str_mv | AT zhujunyi fromsystemictoregionalpersonalhealthandmedicalmonitoringsystemsthatadapttoindividualvariance |