Mobile Systems as a Challenge for Neurological Diseases Management – The Case of Parkinson's Disease

A holistic approach to assess the feasability of telehealth for Parkinson's disease management

“…PD patients normally visit their specialised clinician or GP every 4-6 months. As a result, any change in the patient's conditions may not be recognised for several months, unless the patients themselves make contact [3], [288]. Apart from the visits to the hospital, patients are frequently asked to selfreport their health status, for example, by asking patients to recall the number of On and Off hours (motor fluctuations).…”

“…Besides, they can be time consuming and could be biased by subjectivity issues related to historical information. Moreover, the pattern and severity of PD symptoms may vary considerably during the day and finally, measurements of motor fluctuations made in the clinic may not accurately reflect the actual function al disability experienced by the patient at home [3]. Over the past decades various technologies, methodologies and systems have been developed and used to connect doctors and patients aiming at providing useful tools able to transmit information about the status of the patient to the doctor, generally known as teleconsultancy services [3].…”

“…patients often have difficulty distinguishing and assessing symptoms), recall bias (the patients do not remmember exactly the duration, frequency and severity of the symptoms), it is highly subjective (specially in untrained people) and finally all the collected information it is difficult to analyse (it requires time and a huge effort). Another approach is the use of patient diaries on notebooks, which can improve reliability by recording symptoms as they occur, but does not capture many of the features useful in clinical decision making [3], [289]. Moreover, understanding the process is not an easy task and it even a more challenguing task due to the time restrictions on the office visits.…”

“…And, at the same time, enable the clinicians to manage more efficiently the patient by providing timely indications on the effectiveness of the therapy and suggestions on therapy changes. Patients will greatly benefit from a quantitative objective assessment tool of their motor status in daily life in relation to the dosing schedule [3].…”

“…Furthermore, the current challenge is not only to transmit data, but analyze it and use it appropriately in the prevention, prediction and support of diseases and at the same time, to merge different data sources in order to integrate the knowledge from the diverse sources of information. In this sense, novel statistics methods and machine learning methodologies can contribute to properly analyze and extract knowledge from the data collected [3]. According to Bonato, researchers have focused on three main areas of work to develop tools of clinical interest [293]:…”