Technology and Parkinson: INESC TEC supports Professionals and Patients

By Adriana Arrais and Duarte Dias, researchers at the Centre for Biomedical Engineering Research (CBER), and João Paulo Cunha, C-BER Coordinator

Parkinson’s disease is a neurodegenerative disorder, and the second most common after Alzheimer’s disease; the global incidence is increasing at a faster rate than any other neurological disorder. It is incurable at the time, and the existing treatments focus on reducing the limitations caused by the symptoms.

It is widely known that the usual monitoring of patients, and the assessment of the condition and progression of the issue take place during medical appointments. According to a broader depiction of what takes place during those appointments, it is common for the doctor to listen to the patients’ detailed reports of their symptoms and concerns, perform physical examinations to determine the stage of the disease, and based on this information, maintain or adjust the patient’s therapy.

The monitoring process during the appointments features certain limitations. For instance, the fact that said appointments are not scheduled regularly. Moreover, medical evaluation is subjective, varying depending on the perception and experience of each healthcare professional. Another factor to consider is the qualitative description provided by the patients, influenced by their personal perception. These barriers pose a challenge to the assessment of the patient’s condition over time, which has led to the development of complementary and more quantitative monitoring strategies for better patient management throughout the course of the disease.

What do these solutions consist of?

The development of these solutions focuses on the use of wearable devices that allow non-invasive and wireless measurement of movement signals. These devices range from watches to simple bands with inserted electronics in textiles, placed on one or more limbs.

The quantification of symptoms is often based on the scales followed by doctors to evaluate their patients, using computational learning methods. The monitoring actions can either be continuous or periodical. Both methods can provide the patients’ feedback when they are at home, like the physical evaluation during their medical appointments.

What will they enable?

Considering medical practice, this type of solution will bring significant benefits, particularly the possibility of having objective support in the physical evaluation during appointments, by providing a quantified assessment of symptoms. The data collected at home complements the assessment during said appointments. This additional information allows for a deeper understanding of disease patterns, optimising treatment in a patient-specific manner.

Patients will benefit from a better quality of life because of the possibility of receiving more personalised and tailored treatment that more effectively controls their symptoms. If the solution includes a patient interface, such as a mobile application, it will enable greater patient engagement in their treatment, allowing for a better understanding of their condition.

Until someone finds the cure for the disease, quantified monitoring of symptoms provides great hope for doctors to provide better treatment to their patients. Consequently, it will favour a better quality of life for patients, which is the ultimate goal of Parkinson’s disease treatments.

Challenges

There is still a lot of work to do to make this type of tool a widespread practice in the daily lives of neurologists and Parkinson’s disease patients.

In technical terms, there are some challenges regarding continuous data collection, like distinguishing random everyday movements from moments characterised by significant symptoms. Another limitation is the challenge of obtaining data from all levels of severity, since most patients exhibit symptoms of intermediate severity.

From a global perspective, continuous work is needed to overcome technical challenges and optimise the use of this type of technology. This involves the development of more accurate quantification and the creation of informative and intuitive interfaces. Additionally, it is crucial to develop solutions according to the patients’ convenience, to interfere as little as possible with their daily lives.

At INESC

In the BRAIN laboratory of C-BER, research and development related to Parkinson’s disease have been taking place for about nine years (since 2014), focusing on the quantification of motor symptoms of the disease – always with a strong relationship with the Centro Hospitalar Universitário de São João (CHUSJ), which is crucial to the progress of these endeavours.

It all started with a conversation with doctors on how we could support them in a practice carried out during deep brain stimulation surgeries – the placement of deep electrodes in the brain for stimulation and consequent reduction of motor symptoms. After several iterations, a system consisting of a wearable and a mobile application was developed, which classified the improvement of rigidity during these surgeries while the patient is awake in the operating room. This method allows for optimising the location and configuration of stimulation to achieve the best clinical outcome. These developments resulted in the creation of a patented wearable device and quantification algorithm, both already licensed to the spinoff company InSignals Neurotech – which is preparing European-wide clinical studies for clinical validation of the solution.

Currently, we are using the same wearable device, but we have expanded the focus to the development of a system that incorporates a mobile application with integrated quantification algorithms for various motor symptoms (for medical and patient use), and a platform for healthcare professionals to analyse their patients’ data. For this study, we once again rely on CHUSJ, where we are conducting a joint study and collecting weekly movement data from Parkinson’s patients to develop algorithms for symptom quantification. Soon, we plan to test the results obtained, both at the hospital and at patients’ homes, in order to assess the viability of independent use of this technology by the patients.

By designing a solution that is as flexible as possible for use in a clinical context or at home, the aim is to provide a more comprehensive solution than any available so far, for better patients’ treatment and management.