October 18, 2023
In a brand new research, well being expertise firm Aparito investigated using Garmin health trackers to evaluate sleep quality¹ in people affected by adult-onset idiopathic remoted focal cervical dystonia (AOIFCD). AOIFCD is a neurological dysfunction characterised by involuntary neck spasms that may considerably impression sleep. With sleep-related challenges reported by as much as 70% of AOIFCD sufferers, this research aimed to offer a extra accessible different to smaller polysomnography research. By evaluating sleep structure, researchers sought to achieve beneficial insights into the sleep patterns of AOIFCD sufferers utilizing broadly accessible health trackers.
Individuals within the research used Garmin vívosmart® 4 health trackers and their information seamlessly uploaded to Atom5™, Aparito’s app, through the Garmin Well being SDK. This allowed uncooked information to be collected remotely, lowering the time and prices concerned for members and clinicians compared with an in-clinic research.
Connecting Sufferers and Analysts By Garmin
The research concerned two cohorts of members: one group with identified AOIFCD and one age and sex-matched, unaffected management group. Individuals of the research wore a Garmin vívosmart® 4 health tracker repeatedly over 7 days to file sleep monitoring metrics; specifically, whole sleep time and time spent in non-REM sleep. Accelerometer and coronary heart charge information1 had been recorded through the health tracker and despatched to the Oxygen by Aparito app. Integration of the Garmin Well being SDK inside the app’s platform linked the vívosmart® 4 on to the app and allowed for uncooked information assortment on accelerometry. This was used to determine daytime sleepiness and enabled well being metrics to be captured by the health tracker and subsequently processed inside the platform, permitting analysts to match the essential uncooked information. Knowledge may then be in contrast between the 2 cohorts to determine any variations in sleep high quality, supported by affected person reported outcomes (PROs) submitted by means of the app.
Outcomes from the research have emphasised the necessity for clinicians to display screen for sleep disturbances as a part of routine scientific assessments, notably as a result of sleep monitoring could also be vital for prevention and administration of non-motor signs. The research discovered that common health trackers might be helpful for estimating sleep patterns in sufferers with dystonia. They confirmed with goal measures (beforehand it was performed subjectively by asking them how that they had slept) that these with it had totally different sleep patterns in comparison with wholesome people. Folks with AOIFCD slept longer and had extra non-REM sleep. The research means that these sleep modifications may be linked to issues in particular mind circuits and serotonin exercise, which might be associated to each motion and sleep points in dystonia. This was the primary research demonstrating this impact with goal shopper wearables in a scientific setting.
Adapting Garmin Gadgets for Additional Research
Aparito has quite a few upcoming initiatives using Garmin health trackers and metrics. The power to specifically configure Garmin units to the totally different necessities of every research was key for Aparito of their selection of collaborator. Integration of the Garmin Well being SDK allows the Atom5™ platform to do exactly this, permitting Aparito to customise which well being metrics are to be captured to attain probably the most insightful and correct outcomes.
To be taught extra about Aparito initiatives with Garmin, learn the story about distant affected person monitoring and oncology scientific trial alternatives right here. Or try all research, together with Garmin units on our Garmin Well being Third-party Research Overview web page.
1Garmin smartwatches usually are not designed or meant to watch or diagnose ailments or any medical circumstances. Discover data on metric accuracy right here.
See https://pubmed.ncbi.nlm.nih.gov/36414751/