Abstract
One of the symptoms of Parkinson’s disease is the occurrence of problems with the expression of emotions on the face, called facial masking, facial bradykinesia or hypomimia. Recent medical studies show that this symptom can be used in the diagnosis of this disease. In the presented study, the authors, on the basis of their own research, try to answer the question of whether it is possible to build an automatic Parkinson’s disease recognition system based on the face image. The research used image recordings in the field of visible light and infrared. The material for the study consisted of registrations in a group of patients with Parkinson’s disease and a group of healthy patients. The patients were asked to express a neutral facial expression and a smile. In the detection, both geometric and holistic methods based on the use of convolutional network and image fusion were used. The obtained results were assessed quantitatively using statistical measures, including F1score, which was a value of 0.941. The results were compared with a competitive work on the same subject. A novelty of our experiments is that patients with Parkinson’s disease were in the so-called ON phase, in which, due to the action of drugs, the symptoms of the disease are reduced. The results obtained seem to be useful in the process of early diagnosis of this disease, especially in times of remote medical examination.
Highlights
IntroductionContemporary diagnosis of Parkinson’s disease (PD) is based on a direct clinical picture and medical history
Studies on hypomimia in patients suffering from Parkinson’s disease have been conducted for many years [6,22,23,24]. Their results show that, in general, PD patients show a reduced ability to spontaneously express their faces in everyday situations and in various experiments, including those designed to evoke emotional facial expressions
In their research, including 75 PD patients, they investigated the relationship between hypomimia and the occurrence of motor and non-motor symptoms and achieved a high correlation with clinical evaluation performed using the UPDRS test and other tests
Summary
Contemporary diagnosis of Parkinson’s disease (PD) is based on a direct clinical picture and medical history. Its basis is the finding of the coexistence of the following symptoms: muscular stiffness, tremor of the limbs, slowness and postural disorders. It is estimated that more than 10 million people worldwide suffer from the disease [1], especially after the age of 50 [2]. Making a diagnosis in the case of advanced Parkinson’s disease is not difficult for medical doctors and is based on visible clinical signs. The real problem is the correct diagnosis made at an early stage of the disease when the severity of the classic symptoms is small. It is estimated that incorrect diagnosis can occur in about 10–25% of cases [2,3]
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