Assigning UPDRS Scores in the Leg Agility Task of Parkinsonians: Can It Be Done through BSN-based Kinematic Variables?

In this paper, by characterizing the Leg Agility (LA) task, which contributes to the evaluation of the degree of severity of the Parkinson's Disease (PD), through kinematic variables (including the angular amplitude and speed of thighs' motion), we investigate the link between these variables and Unified Parkinson's Disease Rating Scale (UPDRS) scores. Our investigation relies on the use of a few body-worn wireless inertial nodes and represents a first step in the design of a portable system, amenable to be integrated in Internet of Things (IoT) scenarios, for automatic detection of the degree of severity (in terms of UPDRS score) of PD. The experimental investigation is carried out considering 24 PD patients.Comment: 10 page

Analysis and Visualization of 3D Motion Data for UPDRS Rating of Patients with Parkinson's Disease

Remote monitoring of Parkinson's Disease (PD) patients with inertia sensors is a relevant method for a better assessment of symptoms. We present a new approach for symptom quantification based on motion data: the automatic Unified Parkinson Disease Rating Scale (UPDRS) classification in combination with an animated 3D avatar giving the neurologist the impression of having the patient live in front of him. In this study we compared the UPDRS ratings of the pronation-supination task derived from: (a) an examination based on video recordings as a clinical reference;(b) an automatically classified UPDRS;and (c) a UPDRS rating from the assessment of the animated 3D avatar. Data were recorded using Magnetic, Angular Rate, Gravity (MARG) sensors with 15 subjects performing a pronation- supination movement of the hand. After preprocessing, the data were classified with a J48 classifier and animated as a 3D avatar. Video recording of the movements, as well as the 3D avatar, were examined by movement disorder specialists and rated by UPDRS. The mean agreement between the ratings based on video and (b) the automatically classified UPDRS is 0.48 and with (c) the 3D avatar it is 0.47. The 3D avatar is similarly suitable for assessing the UPDRS as video recordings for the examined task and will be further developed by the research team

Fully immersive virtual reality exergames with dual-task components for patients with Parkinsons disease: a feasibility study

Abstract Background Dual-task training in Parkinsons disease (PD) improves spatiotemporal gait parameters, cognition, and quality of life. Virtual reality (VR) has been used as a therapeutic tool for patients to participate in activities in a safe environment, engage in multisensory experiences, and improve motivation and interest in rehabilitation. This study aimed to investigate the feasibility of fully immersive VR exergames with dual-task components in patients with PD. Methods We developed VR exergames (go/no-go punch game, go/no-go stepping game, and number punch game) to improve habitual behavior control using motor–cognitive dual-task performance in patients with PD. The participants underwent 10 sessions 2–3 times a week, consisting of 30min per session. The Unified Parkinsons Disease Rating Scale, Timed Up and Go test (TUG) under single- and dual-task (cognitive and physical) conditions, Berg balance scale (BBS), Stroop test, trail-making test, and digit span were evaluated before and after intervention. The Simulator Sickness Questionnaire (SSQ) was used to assess VR cybersickness. Usability was assessed using a self-reported questionnaire. Results Twelve patients were enrolled and completed the entire training session. The mean age of participants was 73.83 ± 6.09years; mean disease duration was 128.83 ± 76.96months. The Hoehn and Yahr stages were 2.5 in seven patients and 3 in five patients. A significant improvement was observed in BBS and Stroop color–word test (p = 0.047 and p = 0.003, respectively). TUG time and dual-task interferences showed positive changes, but these changes were not statistically significant. The median SSQ total score was 28.05 (IQR: 29.92), 13.09 (IQR: 11.22), and 35.53 (IQR: 52.36) before, after the first session, and after the final session, respectively; the differences were not significant. Overall satisfaction with the intervention was 6.0 (IQR: 1.25) on a 7-point Likert-type scale. Conclusions Fully immersive VR exergames combined with physical and cognitive tasks may be used for rehabilitation of patients with PD without causing serious adverse effects. Furthermore, the exergames using dual-task components improved executive function and balance. Further development of VR training content may be needed to improve motor and dual-task performances. Trial registration NCT04787549 (https://clinicaltrials.gov/ct2/show/NCT04787549)This study was supported by Grant no. 03-2020-2020 from the Seoul National University Hospital Research Fund

Development of Markerless Systems for Automatic Analysis of Movements and Facial Expressions: Applications in Neurophysiology

This project is focused on the development of markerless methods for studying facial expressions and movements in neurology, focusing on Parkinson’s disease (PD) and disorders of consciousness (DOC). PD is a neurodegenerative illness that affects around 2% of the population over 65 years old. Impairments of voice/speech are among the main signs of PD. This set of impairments is called hypokinetic dysarthria, because of the reduced range of movements involved in speech. This reduction can be visible also in other facial muscles, leading to a hypomimia. Despite the high percentage of patients that suffer from dysarthria and hypomimia, only a few of them undergo speech therapy with the aim to improve the dynamic of articulatory/facial movements. The main reason is the lack of low cost methodologies that could be implemented at home. DOC after coma are Vegetative State (VS), characterized by the absence of self-awareness and awareness of the environment, and Minimally Conscious State (MCS), in which certain behaviors are sufficiently reproducible to be distinguished from reflex responses. The differential diagnosis between VS and MCS can be hard and prone to a high rate of misdiagnosis (~40%). This differential diagnosis is mainly based on neuro-behavioral scales. A key role to plan the rehabilitation in DOC patients is played by the first diagnosis after coma. In fact, MCS patients are more prone to a consciousness recovery than VS patients. Concerning PD the aim is the development of contactless systems that could be used to study symptoms related to speech and facial movements/expressions. The methods proposed here, based on acoustical analysis and video processing techniques could support patients during speech therapy also at home. Concerning DOC patients the project is focused on the assessment of reflex and cognitive responses to standardized stimuli. This would allow objectifying the perceptual analysis performed by clinicians

On the structure of natural human movement

Understanding of human motor control is central to neuroscience with strong implications in the fields of medicine, robotics and evolution. It is thus surprising that the vast majority of motor control studies have focussed on human movement in the laboratory while neglecting behaviour in natural environments. We developed an experimental paradigm to quantify human behaviour in high resolution over extended periods of time in ecologically relevant environments. This allows us to discover novel insights and contradictory evidence to well-established findings obtained in controlled laboratory conditions. Using our data, we map the statistics of natural human movement and their variability between people. The variability and complexity of the data recorded in these settings required us to develop new tools to extract meaningful information in an objective, data-driven fashion. Moving from descriptive statistics to structure, we identify stable structures of movement coordination, particularly within the arm-hand area. Combining our data with numerous published findings, we argue that current hypotheses that the brain simplifies motor control problems by dimensionality reduction are too reductionist. We propose an alternative hypothesis derived from sparse coding theory, a concept which has been successfully applied to the sensory system. To investigate this idea, we develop an algorithm for unsupervised identification of sparse structures in natural movement data. Our method outperforms state-of-the-art algorithms for accuracy and data-efficiency. Applying this method to hand data reveals a dictionary of \emph{sparse eigenmotions} (SEMs) which are well preserved across multiple subjects. These are highly efficient and invariant representation of natural movement, and suggest a potential higher-order grammatical structure or ``movement language''. Our findings make a number of testable predictions about neural coding of movement in the cortex. This has direct consequences for advancing research on dextrous prosthetics and robotics, and has profound implications for our understanding of how the brain controls our body.Open Acces

The role of pre-supplementary motor area in spatial vector transformation: evidence from Parkinson's disease

This thesis investigated the role of the supplementary motor area (SMA) in visuospatial processing using Parkinson’s disease (PD) patients as a model of pre-supplementary motor area (pre-SMA) dysfunction. The vector transformation hypothesis assumes that visuospatial transformation deficits in PD are a result of impairments in calculating vectors or co-ordinate remapping with a reference frame. These vector transformation processes were investigated in spatial normalisation during mental rotation and showed that PD patients demonstrate slower image normalisation rates indicative of a deficit compares with controls. It was then investigated how far these deficits extend to other vector transformation tasks such as abstract grid navigation. PD patients were less accurate than controls and these deficits were independent of spatial short term memory and serial processing suggesting that PD is associated with spatial transformation deficits. Comparisons of visual vector transformation and auditory vector transformation showed that PD patients were less accurate at visual vector transformation than auditory vector transformation suggesting that vector transformation processes may be more sensitive to the visual domain. The final study was a pilot study to investigate the feasibility of using a cognitive vector transformation task to remediate symptoms of bradykinesia in PD. Modest improvements in movement velocity following the vector transformation task but no significant change in movement velocity following a control task suggests that vector transformation can be used for therapeutic gain