Parkinson is a neurodegenerative disease that, for now, has no cure, but its detection at an early stage can improve the quality of life of affected individuals. In recent years, numerous methods have been developed to facilitate the detection of the disease before clinical symptoms appear in the advanced stages. For example, there is the case of a Scottish nurse who claims to be able to detect this disease through the smell of a sick person. Scientific studies were conducted to validate the idea, but they were more focused on male patients.
Recently, the Massachusetts Institute of Technology (MIT) presented a system capable of discerning the presence and severity of the disease through the patient’s breathing during sleep, although this technique requires the installation of a series of devices and a certain deployment of technology in the patient’s home to successfully carry out the examination.
Now, researchers from the Polytechnic University of Madrid (UPM), Complutense University of Madrid (UCM), University of Zaragoza, and other centers in both cities, have published a study in the International Journal of Environmental Research and Public Health which states that an automatic decision support system has successfully identified, among other healthy subjects with a high success rate, patients suffering from the disease through the analysis of their laughter.
Specifically, the decision support system achieved an 83% accuracy rate for classifying laughter from healthy and sick individuals, using a database of 20,000 samples generated automatically from a group of 120 laughter from healthy subjects and Parkinson’s patients. The laughter was recorded in a study while people watched various humor videos randomly (including jokes and funny monologues). The sessions lasted approximately half an hour. The recorded laughter during that session was manually segmented to generate the data used to train the developed system.
Recording and analyzing a person’s laughter is an easy and simple task that does not require special equipment or significant technological deployment. It is expected that, soon, laughter analysis can be done through an application installed on a mobile phone and that will be able to analyze and produce a reliable result in a few minutes.
These automatic systems for early detection of Parkinson’s disease will help improve the efficiency of available and future therapeutic treatments, which, in turn, will improve the living conditions of affected individuals, reduce and rationalize the use of resources in public and private healthcare systems.
Source: MiMub in Spanish
