Wearable Sensors for Heart Rate May Aid in Early Parkinson’s Diagnosis
People with Parkinson’s disease have less variability in their heart rate than adults of a similar age, and this difference can be detected with noninvasive, wearable sensors, according to a new study.
Because lesser heart rate variability is associated with a greater disease risk, its researchers proposed that measuring such variability may help in diagnosing Parkinson’s at early stages.
The study, “Wearable sensor device-based detection of decreased heart rate variability in Parkinson’s disease,” was published in the Journal of Neural Transmission.
While Parkinson’s is perhaps best-known for motor symptoms like tremor, the disease also can cause a number of nonmotor symptoms, ranging from sleep problems to emotional changes and alterations in blood pressure.
Emerging research has shown that nonmotor symptoms often develop before the onset of characteristic motor symptoms, during the so-called “prodromal” period. As such, monitoring nonmotor symptoms may be useful in the workup that precedes a Parkinson’s disease diagnosis.
Heart rate variability
In a study published in 2016, a research team in Japan reported that people with early Parkinson’s had reduced heart rate variability or HRV. In that study, they relied on assessments done in laboratory settings to measure HRV. Because heart rate can vary considerably throughout the day based on an individual’s activity, however, analyses of HRV based on measures taken during the short time that a patient is in a lab show low reproducibility.
These scientists, with colleagues, analyzed HRV using data from sensors that people wore on their wrists for about 24 hours during a hospital stay between May 2018 and September 2020. Their analysis included 27 people with Parkinson’s disease, as well as 23 people without Parkinson’s as controls.
The two groups were similar in terms of age (average age, early 60s) and sex (slightly more females than males in both groups). No restrictions were placed on an individual’s activity or exercise while being monitored.
Overall heart rate was generally higher among the Parkinson’s patients, though the researchers noted that both groups were within normal ranges.
To assess HRV, the team calculated the standard deviation of normal R-R intervals (SDNN) and coefficient of variation of R-R intervals (CVRR) for every 100 consecutive heart beats. Conceptually, SDNN and CVRR are statistical measures of how much change there is from one heartbeat to the next, in terms of the specific timing of heart contractions.
Of note, while heart rate is the average number of heart beats per minute, heart rate variability is the small difference between each beat. Heart rate variability is calculated based on R-R intervals, which average the difference — the time that passes in milliseconds (ms) — between each successive heart beat.
Both the average SDNN and CVRR were significantly lower in people with Parkinson’s than in controls: 4.4 vs. 9.5 ms and 0.65% vs. 1.15%, respectively.
“Our assessment method was effective in detecting decreased HRV in patients” with Parkinson’s, the researchers wrote.
“Given its easy applicability and non-invasiveness, wearable sensors are also suitable for screening subjects at high risk” for Parkinson’s, they added.
Distinguishing those with Parkinson’s
The team then used a statistical test called area under the receiver operating characteristic curve, or AUC, to assess whether these HRV-related parameters could distinguish between people with or without Parkinson’s. AUC values can range from 0.5 to 1, with higher values indicating a better ability to differentiate between two groups.
The best distinguishing ability was achieved using the minimum values of SDNN and CVRR, with an AUC of 0.9 for both HRV-related measures.
“Although we detected decreased HRV parameters in [Parkinson’s] by evaluating the entire record for approximately 24 h[ours], we found that extracting the minimum or relatively low (the first decile in this study) values of HRV parameters in selected sections resulted in better discrimination” between people with or without Parkinson’s, the researchers concluded.
The scientists noted this study is limited by its small size and by HRV measures taken over one day. They stressed that further investigation is needed to validate these results and confirm the reproducibility of HRV measures assessed using wearable sensors.
To determine its applicability for early diagnosis, “our wearable sensor-based analysis should also be tested in subjects at the prodromal stage” of Parkinson’s, the researchers added.