Researchers are conducting a study assessing the use of different motion-tracking sensors to remotely gather data from Parkinson’s disease patients.
The technology holds the potential to noninvasively monitor Parkinson’s motor symptoms, as well as the effects of medication, over the course of patients’ normal daily lives at home.
The study, “Identification of Motor Symptoms Related to Parkinson Disease Using Motion-Tracking Sensors at Home (KÄVELI): Protocol for an Observational Case-Control Study,” was published in JMIR Research Protocols.
Parkinson’s motor symptoms are usually assessed using the motor part of the Movement Disorders Society — Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). This rating scale requires patients to perform a series of repetitive movements, which are then rated by a clinician from zero (normal) to four (severe) to reflect a patient’s level of motor impairment.
However, this scoring method is not sensitive enough and is dependent on an individual clinician’s observations, making it somewhat subjective and prone to variability.
“The symptoms present during the clinic appointment may not reveal all of the issues that are present at home, and the ability to cope independently may vary substantially between the on and off states,” the researchers wrote.
Antiparkinsonian medications can help control Parkinson’s motor symptoms (on periods), but as the disease progresses, patients typically need to gradually increase the treatment dose for maximum benefit. Even after increasing the dose, they might sometimes experience a reappearance or worsening of symptoms (off periods) due to the diminishing effects of the therapy.
There is an urgent need for developing objective, effective, and convenient measurements to help clinicians accurately identify Parkinson’s motor symptoms.
Besides allowing for the collection of quantifiable data regarding the progression of disease-related symptoms, wearable sensors enable remote monitoring of the patient.
This kind of technology may assist clinicians in recognizing on/off periods, helping them to adjust medication doses and schedule to prevent unexpected worsening of symptoms.
Investigators at Tampere University in Finland designed an observational, prospective, case-control study (NCT03366558), called KÄVELI, to help them find new methods to identify and categorize disease-related motor symptoms.
During the study, patients must wear accelerometers connected to the wrist and sensors built into a mobile phone worn on a belt. Long-term motion tracking measurements are acquired at home while patients are going about their everyday lives.
Scientists want to see if motor symptoms related to different stages of Parkinson’s disease can be identified using motion tracking sensors and if the time at which the antiparkinsonian medicine is taken can be detected from the movement signals.
Movement data collection started a year ago, but participant recruitment is continuing throughout spring of this year.
Researchers plan to enroll 50 early-stage Parkinson’s disease (no abnormal involuntary movements, known as dyskinesia, and no on/off state changes), 50 patients in the later stage of the disease (with dyskinesia and on/off state changes), and 50 healthy individuals used as controls. In 2018, the researchers managed to enrolled 103 people, 66 of whom were diagnosed with Parkinson’s.
Patients first have to complete a telephone screening and visit to the hospital. Background characteristics and disease stage is evaluated in the hospital using UPDRS questionnaires and a standardized 20-step walking test.
Before the walking test, a Movesense smart sensor is attached to the nondominant wrist. In addition, the participant wears a smartphone that has a built-in accelerometer, gyroscope (a device that uses Earth’s gravity to help determine orientation), and phone orientation sensor. Patients must also wear a Forciot smart insole, so that scientists can measure the forces applied on the feet. Based on the questionnaires and walking test study, the physiotherapist classifies the participant into one of the study groups.
After this, participants must wear the smartphone at home for three consecutive days. Due to technical requirements, wrist and insole sensors are only used in the 20-step walking test. The motion-tracking system is not worn during sleep or while showering or swimming.
During the three-day period, the participant records the time at which all Parkinson’s disease medications are taken in a smartphone app, as well as in a paper diary format.
“This manual recording was added, since the patients were having problems using the medication registration button despite the simple user interface. The double registration process ensures that medication intake is recorded as accurately as possible. The subjects also record other events, such as falls and other adverse effects, and feedback in the diary,” the researchers said.
“This study will provide quantitative information on PD [Parkinson’s disease] motor symptoms and their statistical properties. The collected dataset will be used to develop algorithms and create tools for remote monitoring of PD progression by physicians and to assist with adjusting the medication,” they concluded.
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