Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note
Wearable devices are burgeoning, and applications across numerous verticals are emerging, including human performance monitoring, at-home patient monitoring, and health tracking, to name a few. Off-the-shelf wearables have been developed with focus on portability, usability, and low-cost. As such, w...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/12/4579 |
| _version_ | 1797482336011419648 |
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| author | Abhishek Tiwari Raymundo Cassani Shruti Kshirsagar Diana P. Tobon Yi Zhu Tiago H. Falk |
| author_facet | Abhishek Tiwari Raymundo Cassani Shruti Kshirsagar Diana P. Tobon Yi Zhu Tiago H. Falk |
| author_sort | Abhishek Tiwari |
| collection | DOAJ |
| description | Wearable devices are burgeoning, and applications across numerous verticals are emerging, including human performance monitoring, at-home patient monitoring, and health tracking, to name a few. Off-the-shelf wearables have been developed with focus on portability, usability, and low-cost. As such, when deployed in highly ecological settings, wearable data can be corrupted by artifacts and by missing data, thus severely hampering performance. In this technical note, we overview a signal processing representation called the modulation spectrum. The representation quantifies the rate-of-change of different spectral magnitude components and is shown to separate signal from noise, thus allowing for improved quality measurement, quality enhancement, and noise-robust feature extraction, as well as for disease characterization. We provide an overview of numerous applications developed by the authors over the last decade spanning different wearable modalities and list the results obtained from experimental results alongside comparisons with various state-of-the-art benchmark methods. Open-source software is showcased with the hope that new applications can be developed. We conclude with a discussion on possible future research directions, such as context awareness, signal compression, and improved input representations for deep learning algorithms. |
| first_indexed | 2024-03-09T22:31:48Z |
| format | Article |
| id | doaj.art-5797586edd3045fbb3e17cd1a884a38b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T22:31:48Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5797586edd3045fbb3e17cd1a884a38b2023-11-23T18:55:38ZengMDPI AGSensors1424-82202022-06-012212457910.3390/s22124579Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical NoteAbhishek Tiwari0Raymundo Cassani1Shruti Kshirsagar2Diana P. Tobon3Yi Zhu4Tiago H. Falk5Institut National de la Recherche Scientifique, University of Quebec, Montréal, QC H5A 1K6, CanadaMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, QC H3A 2B4, CanadaInstitut National de la Recherche Scientifique, University of Quebec, Montréal, QC H5A 1K6, CanadaFaculty of Engineering, Universidad de Medellín, Medellín 050026, ColombiaInstitut National de la Recherche Scientifique, University of Quebec, Montréal, QC H5A 1K6, CanadaInstitut National de la Recherche Scientifique, University of Quebec, Montréal, QC H5A 1K6, CanadaWearable devices are burgeoning, and applications across numerous verticals are emerging, including human performance monitoring, at-home patient monitoring, and health tracking, to name a few. Off-the-shelf wearables have been developed with focus on portability, usability, and low-cost. As such, when deployed in highly ecological settings, wearable data can be corrupted by artifacts and by missing data, thus severely hampering performance. In this technical note, we overview a signal processing representation called the modulation spectrum. The representation quantifies the rate-of-change of different spectral magnitude components and is shown to separate signal from noise, thus allowing for improved quality measurement, quality enhancement, and noise-robust feature extraction, as well as for disease characterization. We provide an overview of numerous applications developed by the authors over the last decade spanning different wearable modalities and list the results obtained from experimental results alongside comparisons with various state-of-the-art benchmark methods. Open-source software is showcased with the hope that new applications can be developed. We conclude with a discussion on possible future research directions, such as context awareness, signal compression, and improved input representations for deep learning algorithms.https://www.mdpi.com/1424-8220/22/12/4579modulation spectrumwearable devicesquality measurementsignal enhancementfeature engineering |
| spellingShingle | Abhishek Tiwari Raymundo Cassani Shruti Kshirsagar Diana P. Tobon Yi Zhu Tiago H. Falk Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note Sensors modulation spectrum wearable devices quality measurement signal enhancement feature engineering |
| title | Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note |
| title_full | Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note |
| title_fullStr | Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note |
| title_full_unstemmed | Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note |
| title_short | Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note |
| title_sort | modulation spectral signal representation for quality measurement and enhancement of wearable device data a technical note |
| topic | modulation spectrum wearable devices quality measurement signal enhancement feature engineering |
| url | https://www.mdpi.com/1424-8220/22/12/4579 |
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