{ "id": "AIBD-0294", "title": "Fitbit Charge 3 oxygen-variation signals precede COVID-19 exacerbation in 4 of 5 cases and reveal severe sleep apnoea in one patient (DEXTERITY pilot, Kanazawa)", "summary": "Kanazawa pilot, 23 COVID-19 patients (2020): Fitbit oxygen-variation signals preceded 4 of 5 exacerbations (sensitivity 80%); one man's persistent signals led to polysomnography showing severe OSAS.", "date_observed": "2021-09-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Yamagami, Nomura and colleagues published the DEXTERITY pilot in JMIR Formative Research on 16 September 2021. They are at Kanazawa University and Japan Community Health Care Organization (JCHO) Kanazawa Hospital. The study ran from August to November 2020. The individual event is undated. Twenty-three patients with PCR-confirmed COVID-19 wore a Fitbit Charge 3 for 30 days. The investigators defined a high “estimated oxygen variation” (EOV) signal as a significant dip and recovery of the oxygen level within the index period. A prediction counted as successful if the signal appeared within two days before an exacerbation. Exacerbation occurred in six patients (seven events). EOV signals preceded four of five analyzed cases (sensitivity 80%, specificity 90%), better than resting-heart-rate signals (50% and 80%). Separately, patient JCHO-023, a 53-year-old man with hypertension recovered from COVID-19, showed “a long-lasting high EOV signal” from days 18 to 29 without symptoms. The team suspected sleep apnea. A portable polysomnogram (Nihon Kohden SAS-2200) gave a 3% oxygen desaturation index (ODI) of 33.6 per hour, severe obstructive sleep apnea syndrome. The paper reports no treatment for him. The authors note the Fitbit's functions and analysis algorithms were not approved as a medical device at the time. They note that baseline data were short and the five exacerbation cases are too few to generalize. The prediction analysis was defined against outcomes after the fact rather than as live alerts.", "category": "benefit created", "unexpected": true, "purpose": "Fitbit's EOV metric summarizes overnight oxygen variation for consumers. The investigators repurposed it to flag COVID-19 deterioration, and the sleep-apnea finding was incidental to that study aim.", "system": "Fitbit Charge 3 estimated oxygen variation (EOV) and resting heart rate, with investigator-defined signal thresholds", "model_version": "Fitbit Charge 3", "developer": "Fitbit (device and EOV algorithm); Kanazawa University investigators (signal definitions)", "deployer": "Kanazawa University and JCHO Kanazawa Hospital (DEXTERITY pilot, UMIN000041421)", "location": "Kanazawa, Japan", "domain": "Healthcare (infectious disease; sleep medicine)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "One man received a diagnosis of severe obstructive sleep apnea (3% ODI 33.6/h) from an incidental wearable signal. The paper reports no treatment or follow-up for him." }, { "group": "organizational", "depth": null, "reason": "The 80% sensitivity for predicting exacerbation is a retrospective pilot result on five events, which the authors say is too small to generalize. No live alerting or changed care is documented." } ], "ai_role": { "status": "assessed", "statement": "The device produced the EOV values. The investigators' own rule flagged high signals, and clinicians decided to order polysomnography for the sleep-apnea patient. The paper does not say whether Fitbit's EOV estimation uses machine learning and notes the functions were not approved as a medical device. The COVID-19 prediction figures were computed after the outcomes were known, not from alerts acted on in real time." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Yamagami K, Nomura A, Kometani M, Shimojima M, Sakata K, Usui S, Furukawa K, Takamura M, Okajima M, Watanabe K, Yoneda T (2021). Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation. JMIR Formative Research 5(9):e30819 (PMC8448084).", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "Coincidental obstructive sleep apnea syndrome confirmed by polysomnography was detected in 1 patient via consistently high EOV signals." }, { "kind": "peer-reviewed study", "citation": "Yamagami et al. (2021), JMIR Form Res 5(9):e30819, results.", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80%, specificity=90%)" }, { "kind": "peer-reviewed study", "citation": "Yamagami et al. (2021), JMIR Form Res 5(9):e30819, representative case 3 (JCHO-023).", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "His 3% oxygen desaturation index was 33.6 per hour, indicating severe OSAS." }, { "kind": "peer-reviewed study", "citation": "Yamagami et al. (2021), JMIR Form Res 5(9):e30819, limitations.", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "the Fitbit wearable device, including its functions (eg, EOV) and analysis algorithms, was not yet approved as a medical device at the time of this study" } ], "replication": { "produced_by": [ "A Fitbit Charge 3 worn for 30 days by patients with PCR-confirmed COVID-19, giving EOV and resting heart rate", "An investigator-defined high-EOV signal (a significant dip and recovery of the oxygen level within the index period) reviewed by the study team", "Weekly phone calls to discharged patients and access to portable polysomnography" ], "must_hold": [ "Patients can pair the device with a smartphone app (elderly patients unable to use a smartphone were not enrolled)", "Enough baseline data to separate abnormal signals from normal variation, which the authors list as lacking in the 30-day window" ], "echoes": [] }, "paired_incident": null, "headline": "Fitbit Charge 3 signals precede 4 of 5 COVID-19 exacerbations", "metric": "EOV signals preceded four of five analyzed cases (sensitivity 80%, specificity 90%)", "comparator": { "against": "high resting-heart-rate (RHR) signals from the same Fitbit data", "before": "the sensitivity and specificity of high RHR signals were 50% and 80%, respectively", "after": "4 out of 5 cases (sensitivity=80%, specificity=90%)", "basis": "measured", "quote": "We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80%, specificity=90%), whereas the sensitivity and specificity of high RHR signals were 50% and 80%, respectively, both lower than those of high EOV signals.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/" }, "later": { "status": "unknown", "date": null, "note": "No later DEXTERITY publication and no follow-up on patient JCHO-023 was found in the cited paper.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://support.google.com/product-documentation/answer/14816019; https://en.wikipedia.org/wiki/Kanazawa_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0294", "catalog_version": "1.0.0", "source_fingerprint": "1c723e06aa36a32592a37c7e4605951c8f977581c24cf09083e762676a11cecd", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0294-source-0001", "AIBD-0294-source-0002", "AIBD-0294-source-0003", "AIBD-0294-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Fitbit (device and EOV algorithm); Kanazawa University investigators (signal definitions)", "deployer": "Kanazawa University and JCHO Kanazawa Hospital (DEXTERITY pilot, UMIN000041421)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The device produced the EOV values. The investigators' own rule flagged high signals, and clinicians decided to order polysomnography for the sleep-apnea patient. The paper does not say whether Fitbit's EOV estimation uses machine learning and notes the functions were not approved as a medical device. The COVID-19 prediction figures were computed after the outcomes were known, not from alerts acted on in real time." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The device produced the EOV values. The investigators' own rule flagged high signals, and clinicians decided to order polysomnography for the sleep-apnea patient. 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They are at Kanazawa University and Japan Community Health Care Organization (JCHO) Kanazawa Hospital. The study ran from August to November 2020. The individual event is undated. Twenty-three patients with PCR-confirmed COVID-19 wore a Fitbit Charge 3 for 30 days. The investigators defined a high “estimated oxygen variation” (EOV) signal as a significant dip and recovery of the oxygen level within the index period. A prediction counted as successful if the signal appeared within two days before an exacerbation. Exacerbation occurred in six patients (seven events). EOV signals preceded four of five analyzed cases (sensitivity 80%, specificity 90%), better than resting-heart-rate signals (50% and 80%). Separately, patient JCHO-023, a 53-year-old man with hypertension recovered from COVID-19, showed “a long-lasting high EOV signal” from days 18 to 29 without symptoms. The team suspected sleep apnea. A portable polysomnogram (Nihon Kohden SAS-2200) gave a 3% oxygen desaturation index (ODI) of 33.6 per hour, severe obstructive sleep apnea syndrome. The paper reports no treatment for him. The authors note the Fitbit's functions and analysis algorithms were not approved as a medical device at the time. They note that baseline data were short and the five exacerbation cases are too few to generalize. The prediction analysis was defined against outcomes after the fact rather than as live alerts.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One man received a diagnosis of severe obstructive sleep apnea (3% ODI 33.6/h) from an incidental wearable signal. The paper reports no treatment or follow-up for him." }, { "group": "organizational", "reason": "The 80% sensitivity for predicting exacerbation is a retrospective pilot result on five events, which the authors say is too small to generalize. No live alerting or changed care is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": true, "purpose": "Fitbit's EOV metric summarizes overnight oxygen variation for consumers. 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Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation. JMIR Formative Research 5(9):e30819 (PMC8448084).", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "Coincidental obstructive sleep apnea syndrome confirmed by polysomnography was detected in 1 patient via consistently high EOV signals." }, { "kind": "peer-reviewed study", "citation": "Yamagami et al. 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They are at Kanazawa University and Japan Community Health Care Organization (JCHO) Kanazawa Hospital. The study ran from August to November 2020. The individual event is undated. Twenty-three patients with PCR-confirmed COVID-19 wore a Fitbit Charge 3 for 30 days. The investigators defined a high “estimated oxygen variation” (EOV) signal as a significant dip and recovery of the oxygen level within the index period. A prediction counted as successful if the signal appeared within two days before an exacerbation. Exacerbation occurred in six patients (seven events). EOV signals preceded four of five analyzed cases (sensitivity 80%, specificity 90%), better than resting-heart-rate signals (50% and 80%). Separately, patient JCHO-023, a 53-year-old man with hypertension recovered from COVID-19, showed “a long-lasting high EOV signal” from days 18 to 29 without symptoms. The team suspected sleep apnea. 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