New tool for monitoring Parkinson's motor symptoms

Due to the complex and variable symptomatology of Parkinson's disease, accurate and continuous monitoring of symptoms becomes a key aspect to accurately adjust medication and could also be used for symptom monitoring during the validation of new treatments. This context has driven the development of strategies based on the use of portable devices and artificial intelligence techniques for continuous and objective monitoring of symptoms.

One of these new developments is MONIPAR, a technological solution developed by the Instrumentation and Applied Acoustics Research Group of the Polytechnic University of Madrid (UPM) in Spain, which objectively evaluates the motor symptoms of Parkinson's disease.

To do this, the user performs a series of standardized exercises in a guided manner, while the movement signal is recorded with different sensors integrated into a commercial smart watch. This signal is treated with artificial intelligence techniques, obtaining indicators with which it is possible to track the main motor symptoms associated with Parkinson's. Thus, MONIPAR provides a feasible and cost-effective solution for monitoring the evolution of tremor and slowing of movement, some of the most common motor symptoms of Parkinson's.

Parkinson's disease is a neurodegenerative disorder that affects 8.5 million people worldwide. In Spain alone the figure is 160,000 people.

This disease is characterized by the presence of motor symptoms such as difficulty maintaining balance, muscle rigidity, slowness of movement (bradykinesia), or tremors. These symptoms reduce the quality of life of patients and that of the family members who care for them, which justifies the development of tools to improve monitoring of the disease.

Artistic recreation of deficient nerve cells in a case of Parkinson's disease. (Image: Amazings/NCYT)

Currently, the evaluation of the disease is carried out by observing the patient's motor and mental state while performing specific tasks. This method has limitations due to the appreciation of the symptom. Additionally, clinical evaluations typically occur during a small number of office visits per year, making therapeutic adjustment difficult.

For the detection and classification of symptoms using MONIPAR, algorithms have been developed based on artificial intelligence techniques. In this way, it is possible to automatically detect some of the most characteristic symptoms of the disease, such as tremor at rest or slowness of movement (bradykinesia).

MONIPAR is a very accessible mobile health tool, thanks to the fact that it uses devices that are in common use today, such as smartphones and smart watches.

As the researchers point out, “the results we have obtained suggest that the proposed system could be used as a complementary tool for the evaluation of motor symptoms in patients with early-stage Parkinson's disease, providing a feasible and cost-effective solution for ambulatory monitoring. of specific motor symptoms such as rest tremor or bradykinesia.

MONIPAR has been developed within the framework of the doctoral thesis of Luis Sigcha (recently awarded the extraordinary doctoral thesis prize for the 2021-2022 Course at the UPM) within the project “Enabling technologies for the care, monitoring and rehabilitation of patients with Parkinson's (TECA-PARK).

The usability of this tool was validated in the AGE-LAB laboratory of the Massachusetts Institute of Technology (MIT) and was successfully tested in various Parkinson's associations in Spain and Portugal.

In addition, this technology has been awarded the award for the most innovative technologies in the UPM2T Challenge 2022 and is currently being used within the framework of the research project “Digital biomarkers for the evaluation of the motor status of patients with Parkinson's Disease for its application.” clinical and therapeutic.

Sigcha and his colleagues present the technical details of MONIPAR in the academic journal Frontiers in Neurology, under the title ” MONIPAR: movement data collection tool to monitor motor symptoms in Parkinson's disease using smartwatches and smartphones.” (Source: UPM)