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1.
Trials ; 22(1): 910, 2021 Dec 11.
Article in English | MEDLINE | ID: covidwho-1571920

ABSTRACT

BACKGROUND: The COVID-19 pandemic poses challenges for timely outcome assessment in randomized clinical trials (RCT). Our aim was to describe our remote neurocognitive testing (NCT) protocol administered by telephone in patients with Parkinson's disease (PD) and obstructive sleep apnea (OSA). METHODS: We studied PD patients with OSA and Montreal Cognitive Assessment (MoCA) score ≤ 27 participating in a RCT assessing OSA treatment impact on cognition. Trial outcomes included change in MoCA and specific cognitive domains from baseline to 3 and 6 months. With COVID19 pandemic-related restrictions, 3-month visits were converted from in-person to telephone administration with materials mailed to participants for compatible tests and retrieved by courier the same day. In exploratory analyses, we compared baseline vs. 3-month results in the control arm, which were not expected to change significantly (test-re-test), using a paired t-test and assessed agreement with the intraclass correlation coefficient (ICC). RESULTS: Seven participants were approached and agreed to remote NCT at 3-month follow-up. Compared to the in-person NCT control arm group, they were younger (60.6 versus 70.6 years) and had a shorter disease course (3.9 versus 9.2 years). Remote NCT data were complete. The mean test-retest difference in MoCA was similar for in-person and remote NCT control-arm groups (between group difference - 0.69; 95%CI - 3.67, 2.29). Agreement was good for MOCA and varied for specific neurocognitive tests. CONCLUSION: Telephone administration of the MoCA and a modified neurocognitive battery is feasible in patients with PD and OSA. Further validation will require a larger sample size.


Subject(s)
COVID-19 , Parkinson Disease , Sleep Apnea, Obstructive , Cognition , Feasibility Studies , Humans , Pandemics , Parkinson Disease/diagnosis , Parkinson Disease/therapy , SARS-CoV-2 , Sleep Apnea, Obstructive/diagnosis , Sleep Apnea, Obstructive/therapy
2.
J Med Internet Res ; 23(11): e29554, 2021 11 19.
Article in English | MEDLINE | ID: covidwho-1528771

ABSTRACT

BACKGROUND: Masked face is a characteristic clinical manifestation of Parkinson disease (PD), but subjective evaluations from different clinicians often show low consistency owing to a lack of accurate detection technology. Hence, it is of great significance to develop methods to make monitoring easier and more accessible. OBJECTIVE: The study aimed to develop a markerless 2D video, facial feature recognition-based, artificial intelligence (AI) model to assess facial features of PD patients and investigate how AI could help neurologists improve the performance of early PD diagnosis. METHODS: We collected 140 videos of facial expressions from 70 PD patients and 70 matched controls from 3 hospitals using a single 2D video camera. We developed and tested an AI model that performs masked face recognition of PD patients based on the acquisition and evaluation of facial features including geometric and texture features. Random forest, support vector machines, and k-nearest neighbor were used to train the model. The diagnostic performance of the AI model was compared with that of 5 neurologists. RESULTS: The experimental results showed that our AI models can achieve feasible and effective facial feature recognition ability to assist with PD diagnosis. The accuracy of PD diagnosis can reach 83% using geometric features. And with the model trained by random forest, the accuracy of texture features is up to 86%. When these 2 features are combined, an F1 value of 88% can be reached, where the random forest algorithm is used. Further, the facial features of patients with PD were not associated with the motor and nonmotor symptoms of PD. CONCLUSIONS: PD patients commonly exhibit masked facial features. Videos of a facial feature recognition-based AI model can provide a valuable tool to assist with PD diagnosis and the potential of realizing remote monitoring of the patient's condition, especially during the COVID-19 pandemic.


Subject(s)
COVID-19 , Facial Recognition , Parkinson Disease , Artificial Intelligence , Humans , Pandemics , Parkinson Disease/diagnosis , SARS-CoV-2
3.
Sensors (Basel) ; 21(15)2021 Jul 21.
Article in English | MEDLINE | ID: covidwho-1346524

ABSTRACT

Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson's disease (PD) symptoms in real-life conditions. Objective: The objective of our study was to explore the feasibility and usability of an mHealth system for continuous and objective real-life measures of patients' health and functional mobility, in unsupervised settings. Methods: Patients with a clinical diagnosis of PD, who were able to walk unassisted, and had an Android smartphone were included. Patients were asked to answer a daily survey, to perform three weekly active tests, and to perform a monthly in-person clinical assessment. Feasibility and usability were explored as primary and secondary outcomes. An exploratory analysis was performed to investigate the correlation between data from the mKinetikos app and clinical assessments. Results: Seventeen participants (85%) completed the study. Sixteen participants (94.1%) showed a medium-to-high level of compliance with the mKinetikos system. A 6-point drop in the total score of the Post-Study System Usability Questionnaire was observed. Conclusions: Our results support the feasibility of the mKinetikos system for continuous and objective real-life measures of a patient's health and functional mobility. The observed correlations of mKinetikos metrics with clinical data seem to suggest that this mHealth solution is a promising tool to support clinical decisions.


Subject(s)
Mobile Applications , Parkinson Disease , Telemedicine , Feasibility Studies , Humans , Parkinson Disease/diagnosis , Smartphone
4.
J Parkinsons Dis ; 11(s1): S11-S18, 2021.
Article in English | MEDLINE | ID: covidwho-1318376

ABSTRACT

Telemedicine programs are particularly suited to evaluating patients with Parkinson's disease (PD) and other movement disorders, primarily because much of the physical exam findings are visual. Telemedicine uses information and communication technologies to overcome geographical barriers and increase access to healthcare service. It is particularly beneficial for rural and underserved communities, groups that traditionally suffer from lack of access to healthcare. There is a growing evidence of the feasibility of telemedicine, cost and time savings, patients' and physicians' satisfaction, and its outcome and impact on patients' morbidity and quality of life. In addition, given the unusual current situation with the COVID-19 pandemic, telemedicine has offered the opportunity to address the ongoing healthcare needs of patients with PD, to reduce in-person clinic visits, and human exposures (among healthcare workers and patients) to a range of infectious diseases including COVID-19. However, there are still several challenges to widespread implementation of telemedicine including the limited performance of parts of the neurological exam, limited technological savvy, fear of loss of a personal connection, or uneasiness about communicating sensitive information. On the other hand, while we are facing the new wave of COVID-19 pandemic, patients and clinicians are gaining increasing experience with telemedicine, facilitating equity of access to specialized multidisciplinary care for PD. This article summarizes and reviews the current state and future directions of telemedicine from a global perspective.


Subject(s)
Parkinson Disease/diagnosis , Parkinson Disease/therapy , Telemedicine , COVID-19/complications , Health Services Accessibility , Humans , Pandemics
5.
In Vivo ; 35(4): 2327-2330, 2021.
Article in English | MEDLINE | ID: covidwho-1285629

ABSTRACT

BACKGROUND: Accurate assessment of symptoms in Parkinson's disease (PD) is essential for optimal treatment decisions. During the past few years, different monitoring modalities have started to be used in the everyday clinical practice, mainly for the evaluation of motor symptoms. However, monitoring technologies for PD have not yet gained wide acceptance among physicians, patients, and caregivers. The COVID-19 pandemic disrupted the patients' access to healthcare, bringing to the forefront the need for wearable sensors, which provide effective remote symptoms' evaluation and follow-up. CASE REPORT: We report two cases with PD, whose symptoms were monitored with a new wearable CE-marked system (PDMonitor®), enabling appropriate treatment modifications. CONCLUSION: Objective assessment of the patient's motor symptoms in his daily home environment is essential for an accurate monitoring in PD and enhances treatment decisions.


Subject(s)
COVID-19 , Parkinson Disease , Wearable Electronic Devices , Humans , Pandemics , Parkinson Disease/diagnosis , Parkinson Disease/epidemiology , Parkinson Disease/therapy , SARS-CoV-2
6.
Neurol Sci ; 42(8): 3089-3092, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1245657

ABSTRACT

BACKGROUND: Falls could be serious events in Parkinson's disease (PD). Patient remote monitoring strategies are on the raise and may be an additional aid in identifying patients who are at risk of falling. The aim of the study was to evaluate if balance and timed-up-and-go data obtained by a smartphone application during COVID-19 lockdown were able to predict falls in PD patients. METHODS: A cohort of PD patients were monitored for 4 weeks during the COVID-19 lockdown with an application measuring static balance and timed-up-and-go test. The main outcome was the occurrence of falls (UPDRS-II item 13) during the observation period. RESULTS: Thirty-three patients completed the study, and 4 (12%) reported falls in the observation period. The rate of falls was reduced with respect to patient previous falls history (24%). The stand-up time and the mediolateral sway, acquired through the application, differed between "fallers" and "non-fallers" and related to the occurrence of new falls (OR 1.7 and 1.6 respectively, p < 0.05), together with previous falling (OR 7.5, p < 0.01). In a multivariate model, the stand-up time and the history of falling independently related to the outcome (p < 0.01). CONCLUSIONS: Our study provides new data on falls in Parkinson's disease during the lockdown. The reduction of falling events and the relationship with the stand-up time might suggest that a different quality of falls occurs when patient is forced to stay home - hence, clinicians should point their attention also on monitoring patients' sit-to-stand body transition other than more acknowledged features based on step quality.


Subject(s)
COVID-19 , Parkinson Disease , Communicable Disease Control , Gait , Gait Analysis , Humans , Parkinson Disease/complications , Parkinson Disease/diagnosis , Postural Balance , SARS-CoV-2 , Smartphone , Time and Motion Studies
7.
Curr Opin Neurol ; 34(4): 589-597, 2021 08 01.
Article in English | MEDLINE | ID: covidwho-1228582

ABSTRACT

PURPOSE OF REVIEW: The COVID-pandemic has facilitated the implementation of telemedicine in both clinical practice and research. We highlight recent developments in three promising areas of telemedicine: teleconsultation, telemonitoring, and teletreatment. We illustrate this using Parkinson's disease as a model for other chronic neurological disorders. RECENT FINDINGS: Teleconsultations can reliably administer parts of the neurological examination remotely, but are typically not useful for establishing a reliable diagnosis. For follow-ups, teleconsultations can provide enhanced comfort and convenience to patients, and provide opportunities for blended and proactive care models. Barriers include technological challenges, limited clinician confidence, and a suboptimal clinician-patient relationship. Telemonitoring using wearable sensors and smartphone-based apps can support clinical decision-making, but we lack large-scale randomized controlled trials to prove effectiveness on clinical outcomes. Increasingly many trials are now incorporating telemonitoring as an exploratory outcome, but more work remains needed to demonstrate its clinical meaningfulness. Finding a balance between benefits and burdens for individual patients remains vital. Recent work emphasised the promise of various teletreatment solutions, such as remotely adjustable deep brain stimulation parameters, virtual reality enhanced exercise programs, and telephone-based cognitive behavioural therapy. Personal contact remains essential to ascertain adherence to teletreatment. SUMMARY: The availability of different telemedicine tools for remote consultation, monitoring, and treatment is increasing. Future research should establish whether telemedicine improves outcomes in routine clinical care, and further underpin its merits both as intervention and outcome in research settings.


Subject(s)
COVID-19 , Parkinson Disease , Telemedicine , Humans , Pandemics , Parkinson Disease/diagnosis , Parkinson Disease/therapy , SARS-CoV-2
8.
J Parkinsons Dis ; 11(3): 971-992, 2021.
Article in English | MEDLINE | ID: covidwho-1201362

ABSTRACT

Sleep disturbances are among the common nonmotor symptoms in patients with Parkinson's disease (PD). Sleep can be disrupted by nocturnal motor and nonmotor symptoms and other comorbid sleep disorders. Rapid eye movement sleep behavior disorder (RBD) causes sleep-related injury, has important clinical implications as a harbinger of PD and predicts a progressive clinical phenotype. Restless legs syndrome (RLS) and its related symptoms can impair sleep initiation. Excessive daytime sleepiness (EDS) is a refractory problem affecting patients' daytime activities. In particular, during the COVID-19 era, special attention should be paid to monitoring sleep problems, as infection-prevention procedures for COVID-19 can affect patients' motor symptoms, psychiatric symptoms and sleep. Therefore, screening for and managing sleep problems is important in clinical practice, and the maintenance of good sleep conditions may improve the quality of life of PD patients. This narrative review focused on the literature published in the past 10 years, providing a current update of various sleep disturbances in PD patients and their management, including RBD, RLS, EDS, sleep apnea and circadian abnormalities.


Subject(s)
Disorders of Excessive Somnolence , Parkinson Disease , REM Sleep Behavior Disorder , Restless Legs Syndrome , Sleep Apnea Syndromes , Sleep Disorders, Circadian Rhythm , COVID-19 , Disorders of Excessive Somnolence/diagnosis , Disorders of Excessive Somnolence/etiology , Disorders of Excessive Somnolence/therapy , Humans , Parkinson Disease/complications , Parkinson Disease/diagnosis , Parkinson Disease/therapy , REM Sleep Behavior Disorder/diagnosis , REM Sleep Behavior Disorder/etiology , REM Sleep Behavior Disorder/therapy , Restless Legs Syndrome/diagnosis , Restless Legs Syndrome/etiology , Restless Legs Syndrome/therapy , Sleep Apnea Syndromes/diagnosis , Sleep Apnea Syndromes/etiology , Sleep Apnea Syndromes/therapy , Sleep Disorders, Circadian Rhythm/diagnosis , Sleep Disorders, Circadian Rhythm/etiology , Sleep Disorders, Circadian Rhythm/therapy
10.
J Parkinsons Dis ; 11(s1): S83-S93, 2021.
Article in English | MEDLINE | ID: covidwho-1122450

ABSTRACT

Remote and objective assessment of the motor symptoms of Parkinson's disease is an area of great interest particularly since the COVID-19 crisis emerged. In this paper, we focus on a) the challenges of assessing motor severity via videos and b) the use of emerging video-based Artificial Intelligence (AI)/Machine Learning techniques to quantitate human movement and its potential utility in assessing motor severity in patients with Parkinson's disease. While we conclude that video-based assessment may be an accessible and useful way of monitoring motor severity of Parkinson's disease, the potential of video-based AI to diagnose and quantify disease severity in the clinical context is dependent on research with large, diverse samples, and further validation using carefully considered performance standards.


Subject(s)
Artificial Intelligence , Parkinson Disease/diagnosis , Telemedicine/methods , Video Recording , Humans , Movement , Parkinson Disease/physiopathology , Severity of Illness Index
11.
J Parkinsons Dis ; 11(s1): S11-S18, 2021.
Article in English | MEDLINE | ID: covidwho-1083887

ABSTRACT

Telemedicine programs are particularly suited to evaluating patients with Parkinson's disease (PD) and other movement disorders, primarily because much of the physical exam findings are visual. Telemedicine uses information and communication technologies to overcome geographical barriers and increase access to healthcare service. It is particularly beneficial for rural and underserved communities, groups that traditionally suffer from lack of access to healthcare. There is a growing evidence of the feasibility of telemedicine, cost and time savings, patients' and physicians' satisfaction, and its outcome and impact on patients' morbidity and quality of life. In addition, given the unusual current situation with the COVID-19 pandemic, telemedicine has offered the opportunity to address the ongoing healthcare needs of patients with PD, to reduce in-person clinic visits, and human exposures (among healthcare workers and patients) to a range of infectious diseases including COVID-19. However, there are still several challenges to widespread implementation of telemedicine including the limited performance of parts of the neurological exam, limited technological savvy, fear of loss of a personal connection, or uneasiness about communicating sensitive information. On the other hand, while we are facing the new wave of COVID-19 pandemic, patients and clinicians are gaining increasing experience with telemedicine, facilitating equity of access to specialized multidisciplinary care for PD. This article summarizes and reviews the current state and future directions of telemedicine from a global perspective.


Subject(s)
Parkinson Disease/diagnosis , Parkinson Disease/therapy , Telemedicine , COVID-19/complications , Health Services Accessibility , Humans , Pandemics
12.
J Parkinsons Dis ; 11(s1): S35-S47, 2021.
Article in English | MEDLINE | ID: covidwho-1058392

ABSTRACT

The increasing prevalence of neurodegenerative conditions such as Parkinson's disease (PD) and related mobility issues places a serious burden on healthcare systems. The COVID-19 pandemic has reinforced the urgent need for better tools to manage chronic conditions remotely, as regular access to clinics may be problematic. Digital health technology in the form of remote monitoring with body-worn sensors offers significant opportunities for transforming research and revolutionizing the clinical management of PD. Significant efforts are being invested in the development and validation of digital outcomes to support diagnosis and track motor and mobility impairments "off-line". Imagine being able to remotely assess your patient, understand how well they are functioning, evaluate the impact of any recent medication/intervention, and identify the need for urgent follow-up before overt, irreparable change takes place? This could offer new pragmatic solutions for personalized care and clinical research. So the question remains: how close are we to achieving this? Here, we describe the state-of-the-art based on representative papers published between 2017 and 2020. We focus on remote (i.e., real-world, daily-living) monitoring of PD using body-worn sensors (e.g., accelerometers, inertial measurement units) for assessing motor symptoms and their complications. Despite the tremendous potential, existing challenges exist (e.g., validity, regulatory) that are preventing the widespread clinical adoption of body-worn sensors as a digital outcome. We propose a roadmap with clear recommendations for addressing these challenges and future directions to bring us closer to the implementation and widespread adoption of this important way of improving the clinical care, evaluation, and monitoring of PD.


Subject(s)
Monitoring, Physiologic/instrumentation , Parkinson Disease/diagnosis , Wearable Electronic Devices , Humans
13.
J Parkinsons Dis ; 11(2): 431-444, 2021.
Article in English | MEDLINE | ID: covidwho-1045531

ABSTRACT

Studies focusing on the relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19), and Parkinson's disease (PD) have provided conflicting results. We review the literature to investigate: 1) Are PD patients at higher risk for contracting COVID-19 and are there specific contributing factors to that risk? 2) How does COVID-19 affect PD symptoms? 3) How does COVID-19 present in PD patients? 4) What are the outcomes in PD patients who contract COVID-19? 5) What is the impact of COVID-19 on PD care? 6) Does COVID-19 increase the risk of developing PD? A literature search was performed from 1979 to 2020 using the terms: 'Parkinson's disease' and 'parkinsonism' combined with: 'COVID-19'; 'SARS-CoV-2' and 'coronavirus'. It does not appear that PD is a specific risk factor for COVID-19. There is evidence for direct/indirect effects of SARS-CoV-2 on motor/non-motor symptoms of PD. Although many PD patients present with typical COVID-19 symptoms, some present atypically with isolated worsening of parkinsonian symptoms, requiring increased anti-PD therapy and having worse outcomes. Mortality data on PD patients with COVID-19 is inconclusive (ranging from 5.2%to 100%). Patients with advanced PD appear to be particularly vulnerable. Single cases of acute hypokinetic-rigid syndrome have been described but no other convincing data has been reported. The rapidity with which COVID-19 has swept across the globe has favored the proliferation of studies which lack scientific rigor and the PD literature has not been immune. A coordinated effort is required to assimilate data and answer these questions in larger PD cohorts.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Parkinson Disease/diagnosis , Parkinson Disease/epidemiology , Antiparkinson Agents/therapeutic use , COVID-19/drug therapy , Humans , Mortality/trends , Pandemics/prevention & control , Parkinson Disease/drug therapy , Risk Factors
15.
J Parkinsons Dis ; 11(2): 491-495, 2021.
Article in English | MEDLINE | ID: covidwho-1034835

ABSTRACT

People with Parkinson's disease (PwP) have been suggested to be more vulnerable to negative psychological and psycho-social effects of the COVID-19 pandemic. Our aim was to assess the potential impact of the COVID-19 pandemic in PwP. A Danish/Swedish cohort of 67 PwP was analysed. Health-related quality of life (HRQL), depression, anxiety, apathy, sleep and motor symptom-scores were included in the analysis. Additionally, the Danish participants provided free-text descriptions of life during the pandemic. Overall, the participants reported significantly better HRQL during the COVID-19 period compared with before. Reduced social pressure may be part of the explanation. Despite worsened anxiety, night sleep improved.


Subject(s)
COVID-19/epidemiology , COVID-19/psychology , Parkinson Disease/epidemiology , Parkinson Disease/psychology , Quality of Life/psychology , Adult , Aged , Aged, 80 and over , Anxiety/diagnosis , Anxiety/epidemiology , Anxiety/psychology , COVID-19/diagnosis , Cohort Studies , Denmark/epidemiology , Humans , Middle Aged , Pandemics , Parkinson Disease/diagnosis , Sweden/epidemiology
16.
J Alzheimers Dis ; 79(3): 931-948, 2021.
Article in English | MEDLINE | ID: covidwho-1033235

ABSTRACT

Proinflammatory cytokines such as tumor necrosis factor (TNF), with its now appreciated key roles in neurophysiology as well as neuropathophysiology, are sufficiently well-documented to be useful tools for enquiry into the natural history of neurodegenerative diseases. We review the broader literature on TNF to rationalize why abruptly-acquired neurodegenerative states do not exhibit the remorseless clinical progression seen in those states with gradual onsets. We propose that the three typically non-worsening neurodegenerative syndromes, post-stroke, post-traumatic brain injury (TBI), and post cardiac arrest, usually become and remain static because of excess cerebral TNF induced by the initial dramatic peak keeping microglia chronically activated through an autocrine loop of microglial activation through excess cerebral TNF. The existence of this autocrine loop rationalizes post-damage repair with perispinal etanercept and proposes a treatment for cerebral aspects of COVID-19 chronicity. Another insufficiently considered aspect of cerebral proinflammatory cytokines is the fitness of the endogenous cerebral anti-TNF system provided by norepinephrine (NE), generated and distributed throughout the brain from the locus coeruleus (LC). We propose that an intact LC, and therefore an intact NE-mediated endogenous anti-cerebral TNF system, plus the DAMP (damage or danger-associated molecular pattern) input having diminished, is what allows post-stroke, post-TBI, and post cardiac arrest patients a strong long-term survival advantage over Alzheimer's disease and Parkinson's disease sufferers. In contrast, Alzheimer's disease and Parkinson's disease patients remorselessly worsen, being handicapped by sustained, accumulating, DAMP and PAMP (pathogen-associated molecular patterns) input, as well as loss of the LC-origin, NE-mediated, endogenous anti-cerebral TNF system. Adrenergic receptor agonists may counter this.


Subject(s)
Brain Injuries/physiopathology , Neurodegenerative Diseases/physiopathology , Stroke/physiopathology , Tumor Necrosis Factor-alpha/physiology , Alzheimer Disease/diagnosis , Alzheimer Disease/physiopathology , Alzheimer Disease/therapy , Anti-Inflammatory Agents, Non-Steroidal/therapeutic use , Brain/physiopathology , Brain Injuries/diagnosis , Brain Injuries/therapy , COVID-19/diagnosis , COVID-19/physiopathology , COVID-19/therapy , Disease Progression , Etanercept/therapeutic use , Heart Arrest/diagnosis , Heart Arrest/physiopathology , Heart Arrest/therapy , Humans , Locus Coeruleus/physiopathology , Neurodegenerative Diseases/diagnosis , Neurodegenerative Diseases/therapy , Norepinephrine/physiology , Parkinson Disease/diagnosis , Parkinson Disease/physiopathology , Parkinson Disease/therapy , Risk Factors , SARS-CoV-2 , Stroke/diagnosis , Stroke/therapy , Survivors , Tumor Necrosis Factor-alpha/antagonists & inhibitors
19.
IEEE Trans Neural Syst Rehabil Eng ; 28(12): 2837-2848, 2020 12.
Article in English | MEDLINE | ID: covidwho-936597

ABSTRACT

Motor disorder is a typical symptom of Parkinson's disease (PD). Neurologists assess the severity of PD motor symptoms using the clinical rating scale, i.e., MDS-UPDRS. However, this assessment method is time-consuming and easily affected by the perception difference of assessors. In the recent outbreak of coronavirus disease 2019, telemedicine for PD has become extremely urgent for clinical practice. To solve these problems, we developed an automated and objective assessment method of the leg agility task in the MDS-UPDRS using videos and a graph neural network. In this study, a sparse adaptive graph convolutional network (SA-GCN) was proposed to achieve fine-grained quantitative assessment of skeleton sequences extracted from videos. Specifically, the sparse adaptive graph convolutional unit with a prior knowledge constraint was proposed to perform adaptive spatial modeling of physical and logical dependency for skeleton sequences, thus achieving the sparse modeling of the discriminative spatial relationships. Subsequently, a temporal context module was introduced to construct the remote context dependency in the temporal dimension, hence determining the global changes of the task. A multi-domain attention learning module was also developed to integrate the static spatial features and dynamic temporal features, and then to emphasize the salient feature selection in the channel domain, thereby capturing the multi-domain fine-grained information. Finally, the evaluation results using a dataset with 148 patients and 870 samples confirmed the effectiveness and reliability of our scheme, and the method outperformed other related state-of-the-art methods. Our contactless method provides a new potential tool for automated PD assessment and telemedicine.


Subject(s)
Leg/physiopathology , Parkinson Disease/diagnosis , Parkinson Disease/physiopathology , Aged , Algorithms , Automation , COVID-19 , Databases, Factual , Female , Humans , Machine Learning , Male , Middle Aged , Movement Disorders/diagnosis , Movement Disorders/etiology , Movement Disorders/physiopathology , Neural Networks, Computer , Parkinson Disease/complications , Psychomotor Performance , Reproducibility of Results , Telemedicine/methods , Video Recording
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