A non-contact system for the assessment of hand motor tasks in people with Parkinson’s disease

Abstract

Clinical diagnosis of Parkinson’s disease (PD) motor symptoms remains a problem. Most of the current studies focus on objective evaluations to make the evaluation more reliable. Most of these systems are based on the use of inertial and electromyographic sensors that require contact with the body part being assessed. Contact sensors restrict natural movement, may be uncomfortable and may require preparation of the body, which may cause irritation. As an alternative to contact sensors for the study of hand motor tasks performed by subjects with and without PD, electrical potential sensing technology is used in this research. A custom hardware has been designed to enable data collection by hand movement. A micro-machine system validated the developed system, and a relationship model was established between hand displacement and non-contact capacitive (NCC) sensor response. An experiment was conducted, including 57 subjects, 30 with PD (experimental group) and 27 healthy control group, followed by an analysis of statistical features extracted from the instantaneous mean frequency (IMNF) of NCC sensor. These results were compared with those obtained from gyroscope signals that are considered in the field to be the gold standard. As a result, NCC responses were correlated linearly with hand displacement (R2 = 0.7692 and $${\text{R}}_{\text{adj}}^{2}$$ R adj 2 = 0.7631). The statistical evaluation of IMNF features showed, that both, contact and non-contact sensors, were able to discriminate movement patterns of the control group from the experimental one. The results confirm statistical similarity between features extracted from NCC and gyroscope signals.

Wrist Movement Variability Assessment in Individuals with Parkinson’s Disease

“…Thus, each pair of sensors defined an axis, with the two perpendicular axes y (radial-ulnar axis) and z (proximal-distal axis). The acquisition system with a 2-D array of four NCC sensors PS25454 was validated by Oliveira et al [ 7 ].…”

“…A Parkinson’s Disease diagnosis is purely clinical and relies on medical history and neurological evaluation [ 7 ]. Clinically, the disease is characterized by four cardinal signs, i.e., bradykinesia, tremor, rigidity, and postural instability.…”

“…Since the last update of MDS-UPDRS, several technological advancements have been developed to aid in obtaining more precise information from patients with PD, including the addition of quantitative measures using various types of signal processing methods and sensors. Electromyography (EMG), electroencephalography (EEG), and inertial sensors are examples of typical quantitative measures [ 13 , 14 , 15 ], but these approaches require careful preparation of the skin, can cause skin irritation, and may not be used in situations with a high risk of contact contamination [ 7 ]. The capacitive measurement is an alternative solution for data collection without requiring contact with the skin and without restricting movement [ 16 ].…”