Wearable technology, especially for neurodegenerative disorders like Parkinson's disease, has been crucial in enabling remote monitoring and accurate, prompt disease management. Wearable sensors, such as gyroscopes, accelerometers, and inertial sensors, provide accurate and continuous symptom monitoring, enabling customised treatment plans and interventions. Sensors such as these offer unbiased information on motor symptoms such tremors, bradykinesia, abnormal gait patterns, and balance problems. With the use of this information, medical professionals may adapt physical therapy, optimise medication regimes, and quickly manage fall risk. Wearable sensors also keep track of non-motor symptoms including sleep disorders and autonomic dysfunction, allowing for early intervention and all-encompassing treatment. The real-time information gathered by wearable sensors also improves patient, carer, and medical professional communication and collaboration.
TopIntroduction
Parkinson's disease is a neurological condition that alters many aspects of gait and ultimately has a negative impact on functional outcomes. Gait patterns are altered throughout the course of the disease leading to decreased functionality; therefore, the focus of healthcare providers revolves around managing and reducing deviations and fluctuations (Poewe et al 2017). Examining Parkinson’s clinically is critical because of limited diagnostic criteria, whereas clinical evaluation is highly influenced by psychological and neuromuscular factors (Kostić, V et al 2016). Some of the initial indicators of Parkinson's disease include tremors and dyskinesia. These are uncontrolled, spontaneous, and abnormal twitching movements affecting the muscles in the face, arms, and legs (Lacono et al 1995). A person with Parkinson's disease often exhibits a distinct shuffling gait and festination, where they take shorter, rapid steps when walking and adopt a hunched posture (Gupta D et al 2011). A key indicator of Parkinson's disease is the occurrence of bradykinesia, a condition marked by abnormally sluggish movements. Freezing of Gait (FOG), which occurs when a patient fails to initiate, maintain, or control their walking pattern, is another frequent prognosis connected to Parkinson's disease. Hypomimia, a lack of facial expression brought on by bradykinesia and muscle stiffness, has been shown to occur (Okuma Y et al. 2008).
Additionally, people with Parkinson's disease frequently have trouble keeping their balance, which makes it difficult for them to stand up straight and prevents them from falling. A precise and thorough assessment and evaluation of the disease and its course is necessary for effective management and treatment options (Hackney et al 2007). The unified PD rating scale (UPDRS) and modified Abnormal Involuntary Movement Scale (mAIMS) are two subjective clinical rating instruments that are commonly used to determine motor impairments. However, both scales are less accurate than inertial sensors because of their subjectivity. The use of inertial sensors for detecting different gait diversifications, bradykinesia, dyskinesia, tremors, and other conditions has become possible due to advancements in technology (Ossig et al. 2016). For tracking motion and measuring spatiotemporal factors like stride length, step length, and cadence throughout the gait, inertial sensors employ gyroscopes and accelerometers. Due to their energy efficiency, simple design, light weight, and user-friendly qualities for monitoring people with medical conditions, wearable sensors in combination with short-range communication technologies like Bluetooth and Zigbee are attracting a lot of attention (Washabaugh et al 2017).
Digital biomarkers are quantifiable, objective physiological, behavioural, or biological data that is gathered and measured via wearable technology. Digital biomarkers are essential for objective assessment, ongoing monitoring, medication optimisation, and tracking the progression of Parkinson's disease. Digital biomarkers provide objective measures of Parkinson's symptoms, reducing subjectivity in diagnosis and monitoring, allowing continuous, real-time monitoring of symptoms like tremors, gait disturbances, and bradykinesia, helping clinicians tailor treatment plans to individual patients, optimizing medication regimens for better symptom management and enable the tracking of disease progression over time, aiding in early detection of changes in symptom severity (Motahari-Nezhad et al., 2021).
Additionally, the significant uptick in research during the previous ten years illustrates the quick development of wearable technology in the field of medicine, both generally and with a focus on Parkinson's disease (PD). Wearable sensors have been proposed and evaluated in numerous studies for the monitoring of various motor and non-motor PD symptoms. Currently, it is crucial to examine and analyse the most recent techniques in-depth.