Parkinson’s disease (PD) stands as the most prevalent movement disorder and the second most common degenerative ailment of the central nervous system, following Alzheimer’s disease. The prevalence of PD is around 1% after the age of 60, escalating to 3% after 80. Detecting PD during its initial stages is difficult and the condition is irreversible. With the rapid advancement of #digitaltechnology, a novel class of biomarkers, known as digital biomarkers, has emerged. “Digital” denotes the methodology of employing sensors and computational tools for data acquisition, which typically encompasses various hardware and software layers. These #digitalbiomarkers possess unique characteristics, such as the capability for longitudinal, continuous measurement and the generation of extensive datasets, sharing similar clinical objectives with traditional biomarkers but offering significant difference
Digital biomarkers encompass objective, quantifiable physiological and behavioral measurements acquired through portable, #wearable, implantable or ingestible #digitaldevices. These measurements are commonly performed using interconnected home products beyond the physical boundaries of clinical environments. The measurement of digital biomarkers is characterized by its non-invasive nature, convenience, suitability for home use, and user-friendliness.
Digital health devices employed for measuring digital biomarkers can be categorized into three main types.
1️⃣ Wearable devices, such as wrist-worn accelerometers, portable #sensors and biometric skin patches.
2️⃣ Smartphones or applications are utilized for detecting voice/speech metrics, #cognitiveevaluations and typing behavior, etc.
3️⃣ Non-visual technologies, which encompass passive measurement without requiring the subject to wear sensors, are implemented in sensor-equipped environments.
Digital biomarker collection can be proactive, where individuals manually input data or perform designated tasks using digital devices. Alternatively, it can be passive, requiring no intervention from the device wearer and gathering data without disrupting the subject’s routine activities, thereby enabling the acquisition of more continuous data.
Read complete report: Digital biomarkers for precision diagnosis and monitoring in Parkinson’s disease.
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