Does deidentification of data from wearable devices give us a false sense of security? A systematic review
Summary: Wearable devices have made it easier to generate and share data collected on individuals. This systematic review seeks to investigate whether deidentifying data from wearable devices is sufficient to protect the privacy of individuals in datasets. We searched Web of Science, IEEE Xplore Dig...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-04-01
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| Series: | The Lancet: Digital Health |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589750022002345 |
| _version_ | 1797861112051400704 |
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| author | Lucy Chikwetu, MSc Yu Miao, BSc Melat K Woldetensae Diarra Bell, BA Daniel M Goldenholz, MD Jessilyn Dunn, PhD |
| author_facet | Lucy Chikwetu, MSc Yu Miao, BSc Melat K Woldetensae Diarra Bell, BA Daniel M Goldenholz, MD Jessilyn Dunn, PhD |
| author_sort | Lucy Chikwetu, MSc |
| collection | DOAJ |
| description | Summary: Wearable devices have made it easier to generate and share data collected on individuals. This systematic review seeks to investigate whether deidentifying data from wearable devices is sufficient to protect the privacy of individuals in datasets. We searched Web of Science, IEEE Xplore Digital Library, PubMed, Scopus, and the ACM Digital Library on Dec 6, 2021 (PROSPERO registration number CRD42022312922). We also performed manual searches in journals of interest until April 12, 2022. Although our search strategy had no language restrictions, all retrieved studies were in English. We included studies showing reidentification, identification, or authentication with data from wearable devices. Our search retrieved 17 625 studies, and 72 studies met our inclusion criteria. We designed a custom assessment tool for study quality and risk of bias assessments. 64 studies were classified as high quality and eight as moderate quality, and we did not detect any bias in any of the included studies. Correct identification rates were typically 86–100%, indicating a high risk of reidentification. Additionally, as little as 1–300 s of recording were required to enable reidentification from sensors that are generally not thought to generate identifiable information, such as electrocardiograms. These findings call for concerted efforts to rethink methods for data sharing to promote advances in research innovation while preventing the loss of individual privacy. |
| first_indexed | 2024-04-09T21:56:49Z |
| format | Article |
| id | doaj.art-d1f009e18d744f12a26bd45f71ef2cf7 |
| institution | Directory Open Access Journal |
| issn | 2589-7500 |
| language | English |
| last_indexed | 2024-04-09T21:56:49Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | The Lancet: Digital Health |
| spelling | doaj.art-d1f009e18d744f12a26bd45f71ef2cf72023-03-24T04:23:19ZengElsevierThe Lancet: Digital Health2589-75002023-04-0154e239e247Does deidentification of data from wearable devices give us a false sense of security? A systematic reviewLucy Chikwetu, MSc0Yu Miao, BSc1Melat K Woldetensae2Diarra Bell, BA3Daniel M Goldenholz, MD4Jessilyn Dunn, PhD5Department of Electrical and Computer Engineering, Duke University, Durham, NC, USADepartment of Biomedical Engineering, Duke University, Durham, NC, USADepartment of Biomedical Engineering, Duke University, Durham, NC, USADepartment of Biomedical Engineering, Duke University, Durham, NC, USADepartment of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USADepartment of Biomedical Engineering, Duke University, Durham, NC, USA; Correspondence to: Dr Jessilyn Dunn, Department of Biomedical Engineering, Duke University, Durham, NC 27708, USASummary: Wearable devices have made it easier to generate and share data collected on individuals. This systematic review seeks to investigate whether deidentifying data from wearable devices is sufficient to protect the privacy of individuals in datasets. We searched Web of Science, IEEE Xplore Digital Library, PubMed, Scopus, and the ACM Digital Library on Dec 6, 2021 (PROSPERO registration number CRD42022312922). We also performed manual searches in journals of interest until April 12, 2022. Although our search strategy had no language restrictions, all retrieved studies were in English. We included studies showing reidentification, identification, or authentication with data from wearable devices. Our search retrieved 17 625 studies, and 72 studies met our inclusion criteria. We designed a custom assessment tool for study quality and risk of bias assessments. 64 studies were classified as high quality and eight as moderate quality, and we did not detect any bias in any of the included studies. Correct identification rates were typically 86–100%, indicating a high risk of reidentification. Additionally, as little as 1–300 s of recording were required to enable reidentification from sensors that are generally not thought to generate identifiable information, such as electrocardiograms. These findings call for concerted efforts to rethink methods for data sharing to promote advances in research innovation while preventing the loss of individual privacy.http://www.sciencedirect.com/science/article/pii/S2589750022002345 |
| spellingShingle | Lucy Chikwetu, MSc Yu Miao, BSc Melat K Woldetensae Diarra Bell, BA Daniel M Goldenholz, MD Jessilyn Dunn, PhD Does deidentification of data from wearable devices give us a false sense of security? A systematic review The Lancet: Digital Health |
| title | Does deidentification of data from wearable devices give us a false sense of security? A systematic review |
| title_full | Does deidentification of data from wearable devices give us a false sense of security? A systematic review |
| title_fullStr | Does deidentification of data from wearable devices give us a false sense of security? A systematic review |
| title_full_unstemmed | Does deidentification of data from wearable devices give us a false sense of security? A systematic review |
| title_short | Does deidentification of data from wearable devices give us a false sense of security? A systematic review |
| title_sort | does deidentification of data from wearable devices give us a false sense of security a systematic review |
| url | http://www.sciencedirect.com/science/article/pii/S2589750022002345 |
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