How to quantify the motor symptoms of Parkinson’s disease

Parkinson’s disease is a degenerative geriatric disease that causes motor and non-motor symptoms and has a major impact on the patient’s life. Recently, due to the development of wearable equipment, there are attempts to objectively quantify the symptoms of the disease. So we looked at how to quantify the symptoms of Parkinson’s disease.

Parkinson’s disease causes dyskinesia due to the loss of dopamine neurons distributed in the black matter of the brain. Initially, hand or arm tremors occur, and symptoms such as stiffness, slow movement, and postural instability occur as the disease progresses. Typical examples include Bradykinesia, Rigidity, Freezing of Gait, and Tremor.

Most of the quantitative studies of bradykinesia used similar methods, which used an angular velocity sensor to calculate the angular velocity and angle of the patient’s movement and then compared the patient’s score with the Unified Parkinson’s Disease Rating Scale (UPDRS).

Parkinson’s disease quantification studies using rigidity are mostly based on load cells and variable resistance. To measure this, a force is applied manually to the patient to measure the viscoelasticity of the patient’s wrist joint or the speed and angle of the wrist movement using an angular velocity / acceleration sensor.

Freezing of gait is a method of quantifying Parkinson’s disease through three-dimensional motion recognition. The developed wearable system measures the patient’s condition in three areas: slow walking, postural instability, and walking speed. The use of a linear accelerometer to detect freezing during the movement of the subject makes it possible to quantify Parkinson’s disease, which has proved practical in clinical applications and research.

People with Parkinson’s disease have tremors that abnormally swing the body, such as the hand, and have regular tremors of 4–6H. This regularity is a good feature to diagnose the disease. Tremor can be measured by using electroencephalogram, EMG signal or angular velocity sensor. EMG signals are used not only to measure progress but also to measure other abnormal motility because it allows you to objectively and accurately determine abnormal movements of muscles.

Spiral drawing is also commonly used as a method of testing the tremors of movement disorders such as Parkinson’s disease. A spiral picture drawn on paper by the subject is scanned with a Hewlett-Packard scanner to calculate the amplitude of the tremor. The function of the continuous rotation angle is calculated as the vacuum signal minus the ‘best-fit spiral-curve’ corresponding to the line drawn along a spiral line drawn at a constant angle. At this time, the maximum amplitude of the vibration between 0 and 1808 degrees of polar angle is determined by the amplitude of the true. The results obtained from further analysis showed a high correlation with actual clinical results as a result of regression analysis with Bain and Findley rating, one of the measures of progress.

Due to differences in dyskinesia among Parkinson’s patients, studies have quantified the disease using a combination of dyskinesia to improve the accuracy of quantification. In addition, there is a method to measure the patient’s Bradykinesia according to the tapping speed by instructing the patient’s response rate and the tapping of the screen according to the signal using the smartphone’s built-in sensor.

When examining the quantification method according to the motor symptoms, the most research in Korea quantified Parkinson’s disease based on exercise relaxation. Overseas research was not much different from domestic research methods in terms of methodology, but the trend of measurement methods was different. We could see papers based on various methods of physical movement and tapping, and the most common method was to measure the patient’s motility by using the acceleration sensor and the angular velocity sensor together.

For continuous monitoring, we need a weighing device that can be used by the patient, but there is relatively little research using smartphones. We believe that quantification methods and research utilizing an accessible and easy-to-use environment for all will be needed.