Home-based digital monitoring discerns motor fluctuation profiles
Smartwatch tech could help 'revolutionize' clinical practice, researchers said
Monitoring symptoms at home using smartwatch-smartphone technology collected individual profiles of tremor and activity fluctuations among people with advanced Parkinson’s disease being treated with levodopa.
The technology can provide useful information to improve treatments and patient outcomes and, by combining it with telemedicine and other digital health tools, could help reduce healthcare costs and the need for medical resources.
“This highlights the potential of [home-based monitoring] using [smartwatch] technology for revolutionizing clinical practices,” the researchers wrote in “Home-based monitoring of persons with advanced Parkinson’s disease using smartwatch-smartphone technology,” which was published in Scientific Reports.
Parkinson’s disease is caused by the dysfunction and death of nerve cells that produce dopamine, a signaling molecule that nerve cells use to communicate with each other. This leads to the disease’s motor symptoms, which include slowed movements (bradykinesia), tremor, rigidity, and balance and walking issues.
These can be eased with levodopa, a molecule used by cells to produce dopamine. Using it long term, however, can cause motor fluctuations, which are marked by on periods, when symptoms are controlled, alternating with off periods, when they recur when the medication wears off, and sudden and uncontrolled movements, called dyskinesia.
Monitoring motor fluctuations
In clinical practice, motor symptoms are usually assessed sporadically, during clinical visits, or subjectively, thereby “preventing the effective monitoring of their progression and … leading to suboptimal treatment/therapeutic choices,” the researchers wrote.
Digital tools may help to quantitatively evaluate motor symptoms. In this study, researchers sought to characterize motor fluctuations in people with advanced Parkinson’s through a home-based monitoring kit that included a smartwatch and a smartphone with a dedicated app. The study included 21 patients with motor fluctuations and levodopa-induced dyskinesia. They were mainly men (17), had a mean age of 66.1, and were living with the disease for a mean of 10.3 years. The patients were being treated with a mean of 5.1 daily doses of levodopa, corresponding to a mean 813 mg daily dose.
The experimental approach started with a clinical visit where participants received the monitoring kit, were explained the protocol, and underwent several cognitive and motor tests.
They also performed a motor task to measure the time it takes to rise from a chair, stand up, walk 3 meters, turn around, walk, and sit back on the chair (time-up-and-go), and tests to assess finger tapping and hand tremor and rotation.
Home monitoring was performed for two weeks. Patients needed to wear the watch during waking hours and perform the motor tasks twice daily, once in an off state and another during an on period. They also had to fill out a daily symptom questionnaire and a two-day symptom diary, wear the watch for two nights, and report on medications.
The patients received two phone calls from the research team for general questions and feedback. The smartwatch had sensors to passively measure data like tremor, dyskinesia, and level of activity using dedicated algorithms. The experiment ended with a clinic visit where patients answered several questionnaires.
There was good compliance with the protocol overall. Most patients wore the watch for more than 12 hours a day and complied well with motor tasks and the questionnaires. Although most didn’t skip more than a few medication doses, most had a delay in the recommended intake time.
The results showed striking differences in individual patterns of tremor fluctuations, which let researchers divide participants into four profiles. These included patients with tremor fluctuations mainly around medication intake when they were presumably in an off period (six patients); those with tremors at specific parts of the day, independent of the medication (two); patients with tremors throughout the day (eight); and those with no regular tremor fluctuations (five).
“We were able to objectively differentiate between [Parkinson’s] patients with tremor responding to [levodopa], and those for which tremor could not serve as a marker for medication-associated [motor fluctuations],” the researchers wrote.
Varying activity levels
The participants’ activity levels also varied, which in some cases was related to tremor. In those with tremors that varied with the medication, activity increased when tremors decreased during on periods. In some cases, activity levels were higher when tremors were less present “even though the fluctuations did not follow medication intakes,” the researchers wrote.
The data suggest that monitoring patients’ activity can provide clinicians with information on their lifestyles and be used to improve individual rehabilitation strategies, the researchers said.
The data obtained for tremors during home monitoring significantly correlated with data assessed with the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), a standard scale to evaluate patients’ symptoms, during the first clinical visit. There were also moderate correlations regarding activity levels and dyskinesia, although they weren’t significant.
Also, according to the answers provided in the diaries, tremor was detected significantly more during patients’ self-reported off periods, and activity levels were higher during self-reported on periods.
“This study provides useful insights into symptoms and fluctuations in activity and symptoms throughout the day, in particular the analytical approach to assess daily symptom fluctuations,” the researchers wrote. Future research to monitor tremor severity, not just tremor presence, and evaluate other motor symptoms, including dyskinesia and bradykinesia, may lead to a broader characterization of individual profiles.
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