Wearable devices are an emerging trend in many fields: from fitness and entertainment to healthcare. In the last years, we have seen a large variety of new devices entering the market. The spread of these devices and their increasing capability of continuously acquiring biological signals allowed researchers and engineers to investigate and develop new methods for healthcare applications. This thesis was carried out in collaboration with S.A.T.E. Systems and Advanced Technologies Engineering S.r.l. . The objective of this thesis is to conduct a detailed analysis of the possible applications of wearable sensing in healthcare. First, a review and analysis of commercially available wearable devices is presented, through market inquiries and literature review. Then some use-cases are addressed employing real data. The data was retrieved from cutting edge commercially available wearable devices such as Apple Watch series 7, an advanced smartwatch capable of recording ECG traces and Oura Ring generation 3, an ultracompact smart-ring able to measure peripheral body temperature. More specifically, biological signals were collected from a set of volunteers and then processed both with proprietary algorithms and state-of-the-art methods. This thesis shows how such data can be used in biometric authentication through ECG signal, employing non-fiducial handcrafted features based on Fourier Transform of beats autocorrelation. Methods for health state prediction by extracting features from skin temperature, heart rate and respiratory rate are also presented.
Wearable devices are an emerging trend in many fields: from fitness and entertainment to healthcare. In the last years, we have seen a large variety of new devices entering the market. The spread of these devices and their increasing capability of continuously acquiring biological signals allowed researchers and engineers to investigate and develop new methods for healthcare applications. This thesis was carried out in collaboration with S.A.T.E. Systems and Advanced Technologies Engineering S.r.l. . The objective of this thesis is to conduct a detailed analysis of the possible applications of wearable sensing in healthcare. First, a review and analysis of commercially available wearable devices is presented, through market inquiries and literature review. Then some use-cases are addressed employing real data. The data was retrieved from cutting edge commercially available wearable devices such as Apple Watch series 7, an advanced smartwatch capable of recording ECG traces and Oura Ring generation 3, an ultracompact smart-ring able to measure peripheral body temperature. More specifically, biological signals were collected from a set of volunteers and then processed both with proprietary algorithms and state-of-the-art methods. This thesis shows how such data can be used in biometric authentication through ECG signal, employing non-fiducial handcrafted features based on Fourier Transform of beats autocorrelation. Methods for health state prediction by extracting features from skin temperature, heart rate and respiratory rate are also presented.
Analysis of Potential Healthcare Applications of Wearable Devices
MEGGIO, LORENZO
2021/2022
Abstract
Wearable devices are an emerging trend in many fields: from fitness and entertainment to healthcare. In the last years, we have seen a large variety of new devices entering the market. The spread of these devices and their increasing capability of continuously acquiring biological signals allowed researchers and engineers to investigate and develop new methods for healthcare applications. This thesis was carried out in collaboration with S.A.T.E. Systems and Advanced Technologies Engineering S.r.l. . The objective of this thesis is to conduct a detailed analysis of the possible applications of wearable sensing in healthcare. First, a review and analysis of commercially available wearable devices is presented, through market inquiries and literature review. Then some use-cases are addressed employing real data. The data was retrieved from cutting edge commercially available wearable devices such as Apple Watch series 7, an advanced smartwatch capable of recording ECG traces and Oura Ring generation 3, an ultracompact smart-ring able to measure peripheral body temperature. More specifically, biological signals were collected from a set of volunteers and then processed both with proprietary algorithms and state-of-the-art methods. This thesis shows how such data can be used in biometric authentication through ECG signal, employing non-fiducial handcrafted features based on Fourier Transform of beats autocorrelation. Methods for health state prediction by extracting features from skin temperature, heart rate and respiratory rate are also presented.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/40251