Intra and inter-rater remote assessment of bradykinesia in Parkinson's disease / Evaluación remota de la bradicinesia en la enfermedad de Parkinson mediante análisis intra e inter evaluadores

Introduction: Reliable assessment of individuals with Parkinson's disease (PD) is essential for providing adequate treatment. Clinical assessment is a complex and time-consuming task, especially for bradykinesia, since its evaluation can be influenced by the degree of experience of the examiner, patient collaboration and individual bias. Improvement of the clinical evaluation can be obtained by considering assessments from several professionals. However, this is only true when inter and intra-rater agreement are high. Recently, the Movement Disorder Society highlighted, during the COVID-19 pandemic, the need to develop and validate technologies for remote assessment of the motor status of people with PD. Thus, this study introduces an objective strategy for the remote evaluation of bradykinesia using multi-specialist analysis. Methods: Twelve volunteers with PD participated and these were asked to execute finger tapping, hand opening/closing and pronation/supination movements. Each task was recorded and rated by fourteen PD health experts for each patient. The scores were assessed on an individual basis. Intra and inter-rater agreement and correlation were estimated. Results: The results showed that agreements and correlations between experienced examiners were high with low variability. In addition, group analysis was noted as possessing the potential to solve individual inconsistency bias. Conclusion: Furthermore, this study demonstrated the need for a group with prior training and experience, along with indicating the importance for the development of a clinical protocol that can use telemedicine for the evaluation of individuals with PD, as well as the inclusion of a specialized mediating group. In Addition, this research helps to the development of a valid remote assessment of bradykinesia.(AU)

Introducción: La evaluación confiable de las personas con la enfermedad de Parkinson (EP) es esencial para lograr con un tratamiento adecuado. La evaluación clínica es una tarea compleja y que requiere mucho tiempo, especialmente para la bradicinesia, ya que su evaluación puede verse influenciada por el grado de experiencia del examinador, la colaboración del paciente y el sesgo individual. La mejora de la evaluación clínica se puede obtener considerando las evaluaciones de varios profesionales. Sin embargo, esto solo es más preciso cuando el convenio intra e inter evaluadores es alto. Recientemente, la Sociedad de Trastornos del Movimiento destacó, durante la pandemia COVID-19, la necesidad de desarrollar y validar tecnologías para la evaluación remota del estado motor de las personas con EP. Por lo tanto, este estudio presenta una estrategia objetiva para la evaluación remota de la bradicinesia mediante un análisis multi evaluadores. Métodos: Participaron 12 voluntarios con EP y se les pidió que ejecutaran movimientos de golpeteo de dedos de las manos, movimientos con las manos y pronación-supinación de las manos. Cada ejecución del movimiento fue registrado y calificado por 14 expertos en salud. Las puntuaciones se evaluaron de forma individual. Se estimó el convenio y la correlación intra e inter evaluadores. Resultados: Los resultados mostraron que los convenios y las correlaciones inter evaluadores experimentados son altos con baja variabilidad. Además, se observó que el análisis de grupo posee el potencial de resolver el sesgo de inconsistencia individual. Conclusiones: De esta forma, este estudio demostró la necesidad de un grupo con formación y experiencia previa, señalando la importancia para el desarrollo de un protocolo clínico que utiliza la telemedicina para la evaluación de personas con EP y como la inclusión de un grupo mediador especializado. En realidad, esta investigación propone una evaluación remota eficaz de la bradicinesia.(AU)

Intra and inter-rater remote assessment of bradykinesia in Parkinson's disease.

INTRODUCTION: Reliable assessment of individuals with Parkinson's disease (PD) is essential for providing adequate treatment. Clinical assessment is a complex and time-consuming task, especially for bradykinesia, since its evaluation can be influenced by the degree of experience of the examiner, patient collaboration and individual bias. Improvement of the clinical evaluation can be obtained by considering assessments from several professionals. However, this is only true when inter and intra-rater agreement are high. Recently, the Movement Disorder Society highlighted, during the COVID-19 pandemic, the need to develop and validate technologies for remote assessment of the motor status of people with PD. Thus, this study introduces an objective strategy for the remote evaluation of bradykinesia using multi-specialist analysis. METHODS: Twelve volunteers with PD participated and these were asked to execute finger tapping, hand opening/closing and pronation/supination movements. Each task was recorded and rated by fourteen PD health experts for each patient. The scores were assessed on an individual basis. Intra and inter-rater agreement and correlation were estimated. RESULTS: The results showed that agreements and correlations between experienced examiners were high with low variability. In addition, group analysis was noted as possessing the potential to solve individual inconsistency bias. CONCLUSION: Furthermore, this study demonstrated the need for a group with prior training and experience, along with indicating the importance for the development of a clinical protocol that can use telemedicine for the evaluation of individuals with PD, as well as the inclusion of a specialized mediating group. In Addition, this research helps to the development of a valid remote assessment of bradykinesia.

Symptom Analysis of Early Parkinson's Disease and its Correlation with High Sensitivity C-reactive Protein.

Parkinson's disease is a debilitating neurodegenerative disease for which there is no cure. It is characterized by bradykinesia, resting tremor, rigidity and postural instability, due to impairment of function of the basal ganglia which is involved in the coordination of body movement. Neuro-inflammation is pathogenesis of development in early Parkinson's disease. High-sensitivity C-reactive protein level is a useful non-specific biochemical marker of inflammation. Objective of this study was to analyze the symptoms of Parkinson disease and it's correlation with high sensitive CRP. Seventy-six Parkinson's disease patients were enrolled in this Cross-sectional observational study that was attended in the Department of Neurology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh from September 2014 to March 2016. Analysis of the symptoms of Parkinson disease and it's correlation with high sensitive CRP were done among these patients. This study was performed on 76 Parkinson disease patients with presented early with symptoms. a positive and highly significant correlation were seen in between duration of tremor and High sensitivity CRP (r=0.430, p<0.001) and between duration of bradykinesia and High sensitivity CRP (r=0.426, p<0.001) which indicate increase duration causes increase level of high-sensitivity C-reactive protein value. The neuro-inflammation plays a significant role in the pathogenesis of symptoms development in early Parkinson's disease.

Functional interaction of abnormal beta and gamma oscillations on bradykinesia in parkinsonian rats.

Bradykinesia, a debilitating symptom characterized by impaired movement initiation and reduced speed in Parkinson's disease (PD), is associated with abnormal oscillatory activity in the motor cortex-basal ganglia circuit. We investigated the interplay between abnormal beta and gamma oscillations in relation to bradykinesia in parkinsonian rats. Our findings showed reduced movement activities in parkinsonian rats, accompanied by enhanced high beta oscillations in the motor cortex, which are closely associated with movement transitional difficulties. Additionally, gamma oscillations correlated with movement velocity in control rats but not in parkinsonian rats. We observed selective coupling between high beta oscillation phase and gamma oscillation amplitude in PD, as well as cortical high beta-broadband gamma phase-amplitude coupling (PAC) negatively influencing locomotor activities in control and PD rats. These findings suggest a collaborative role of cortical beta and gamma oscillations in facilitating movement execution, with beta oscillations being linked to movement initiation and gamma oscillations associated with movement speed. Importantly, the aberrant alterations of these oscillations are closely related to the development of bradykinesia. Furthermore, PAC hold promise as a biomarker for comprehensive assessment of movement performance in PD.

Risk factors for hypoactive delirium in patients with nontraumatic ARDS: a prospective observational study.

To investigate the incidence, characteristics and risk factors for hypoactive delirium in patients with nontraumatic acute respiratory distress syndrome (ARDS) and to explore the independent risk factors associated with hypoactive delirium and provide new ideas for early prediction and treatment. Hypoactive delirium is a known serious complication in ARDS patients, and currently, there are no effective early detection models or clinical prediction tools, and there is a lack of clinical treatment. This study included nontraumatic ARDS patients who stayed in the intensive care unit (ICU) for more than 24 h and were older than 18 years. A total of 205 ARDS patients admitted to the ICU of Gansu Provincial People's Hospital between December 2021 and February 2023 were selected. Demographic data, clinical characteristics and laboratory test results were collected within 24 h after the patients entered the ICU. Multivariate logistic regression analysis was used to investigate risk factors, evaluate the clinical prediction effect of the model and construct a nomogram for visual display. The incidence of hypoactive delirium among the patients included in the study was 41%. Patients with hypoactive delirium had hypertension; diabetes mellitus; Acute Physiology and Chronic Health Evaluation II (APACHE II) scores ≥ 15; and increased procalcitonin, C-reactive protein (CRP), lactic dehydrogenase and interleukin-6 (IL-6) levels compared with those without hypoactive delirium. Logistic regression analysis revealed that diabetes mellitus (OR 3.305, 95% CI: 1.866-12.616; p = 0.047), CRP level (OR 1.002, 95% CI: 1.001-1.023; p = 0.044), and IL-6 level (OR 1.045, 95% CI: 1.017-1.063; p = 0.001) were independent risk factors for hypoactive delirium. After receiver operating characteristic (ROC) curve analysis, calibration plot and decision curve analysis (DCA) confirmed that the clinical prediction ability of this study model was satisfactory, and a nomogram was drawn for visual display. Hypoactive delirium is a common serious complication in nontraumatic ARDS patients. Our logistic regression model not only effectively predicts hypoactive delirium early but also reveals potential clinical therapeutic targets.

Neuronal intranuclear inclusion disease misdiagnosed as Parkinson's disease: a case report.

Neuronal intranuclear inclusion disease (NIID) is a rare progressive neurodegenerative disease that mainly manifests as dementia, muscle weakness, sensory disturbances, and autonomic nervous dysfunction. Herein, we report a 68-year-old Chinese woman who was hospitalized because of resting tremor and bradykinesia that had been present for 7 years. Five years prior, bradykinesia and hypermyotonia had become apparent. She had urinary incontinence and rapid eye movement sleep behavior disorder. She was diagnosed with Parkinson's disease (PD) and received levodopa and pramipexole, which relieved her motor symptoms. During hospitalization, diffusion-weighted imaging revealed a high-intensity signal along the cortical medullary junction. Moreover, a skin biopsy revealed the presence of intranuclear inclusions in adipocytes, fibroblasts, and sweat gland cells. NIID was diagnosed by testing the Notch 2 N-terminal-like C (NOTCH2NLC) gene. We report this case to remind doctors to consider NIID when diagnosing patients with symptoms indicative of Parkinson's disease. Moreover, we note that further research is needed on the mechanism by which levodopa is effective for NIID.

Time-resolved quantification of fine hand movements as a proxy for evaluating bradykinesia-induced motor dysfunction.

Bradykinesia is a behavioral manifestation that contributes to functional dependencies in later life. However, the current state of bradykinesia indexing primarily relies on subjective, time-averaged categorizations of motor deficits, which often yield poor reliability. Herein, we used time-resolved analyses of accelerometer recordings during standardized movements, data-driven factor analyses, and linear mixed effects models (LMEs) to quantitatively characterize general, task- and therapy-specific indices of motor impairment in people with Parkinson's disease (PwP) currently undergoing treatment for bradykinesia. Our results demonstrate that single-trial, accelerometer-based features of finger-tapping and rotational hand movements were significantly modulated by divergent therapeutic regimens. Further, these features corresponded well to current gold standards for symptom monitoring, with more precise predictive capacities of bradykinesia-specific declines achieved when considering kinematic features from diverse movement types together, rather than in isolation. Herein, we report data-driven, sample-specific kinematic profiles of diverse movement types along a continuous spectrum of motor impairment, which importantly, preserves the temporal scale for which biomechanical fluctuations in motor deficits evolve in humans. Therefore, this approach may prove useful for tracking bradykinesia-induced motor decline in aging populations the future.

Slowing of Movements in Healthy Aging as a Rational Economic Response to an Elevated Effort Landscape.

Why do we move slower as we grow older? The reward circuits of the brain, which tend to invigorate movements, decline with aging, raising the possibility that reduced vigor is due to the diminishing value that our brain assigns to movements. However, as we grow older, it also becomes more effortful to make movements. Is age-related slowing principally a consequence of increased effort costs from the muscles, or reduced valuation of reward by the brain? Here, we first quantified the cost of reaching via metabolic energy expenditure in human participants (male and female), and found that older adults consumed more energy than the young at a given speed. Thus, movements are objectively more costly for older adults. Next, we observed that when reward increased, older adults, like the young, responded by initiating their movements earlier. Yet, unlike the young, they were unwilling to increase their movement speed. Was their reluctance to reach quicker for rewards due to the increased effort costs, or because they ascribed less value to the movement? Motivated by a mathematical model, we next made the young experience a component of aging by making their movements more effortful. Now the young responded to reward by reacting faster but chose not to increase their movement speed. This suggests that slower movements in older adults are partly driven by an adaptive response to an elevated effort landscape. Moving slower may be a rational economic response the brain is making to mitigate the elevated effort costs that accompany aging.

Objective clinical registration of tremor, bradykinesia, and rigidity during awake stereotactic neurosurgery: a scoping review.

Tremor, bradykinesia, and rigidity are incapacitating motor symptoms that can be suppressed with stereotactic neurosurgical treatment like deep brain stimulation (DBS) and ablative surgery (e.g., thalamotomy, pallidotomy). Traditionally, clinicians rely on clinical rating scales for intraoperative evaluation of these motor symptoms during awake stereotactic neurosurgery. However, these clinical scales have a relatively high inter-rater variability and rely on experienced raters. Therefore, objective registration (e.g., using movement sensors) is a reasonable extension for intraoperative assessment of tremor, bradykinesia, and rigidity. The main goal of this scoping review is to provide an overview of electronic motor measurements during awake stereotactic neurosurgery. The protocol was based on the PRISMA extension for scoping reviews. After a systematic database search (PubMed, Embase, and Web of Science), articles were screened for relevance. Hundred-and-three articles were subject to detailed screening. Key clinical and technical information was extracted. The inclusion criteria encompassed use of electronic motor measurements during stereotactic neurosurgery performed under local anesthesia. Twenty-three articles were included. These studies had various objectives, including correlating sensor-based outcome measures to clinical scores, identifying optimal DBS electrode positions, and translating clinical assessments to objective assessments. The studies were highly heterogeneous in device choice, sensor location, measurement protocol, design, outcome measures, and data analysis. This review shows that intraoperative quantification of motor symptoms is still limited by variable signal analysis techniques and lacking standardized measurement protocols. However, electronic motor measurements can complement visual evaluations and provide objective confirmation of correct placement of the DBS electrode and/or lesioning. On the long term, this might benefit patient outcomes and provide reliable outcome measures in scientific research.

The sound of Parkinson's disease: A model of audible bradykinesia.

INTRODUCTION: Evaluation of bradykinesia is based on five motor tasks from the MDS-UPDRS. Visually scoring these motor tasks is subjective, resulting in significant interrater variability. Recent observations suggest that it may be easier to hear the characteristic features of bradykinesia, such as the decrement in sound intensity or force of repetitive movements. The objective is to evaluate whether audio signals derived during four MDS-UPDRS tasks can be used to detect and grade bradykinesia, using two machine learning models. METHODS: 54 patients with Parkinson's disease and 28 healthy controls were filmed while executing the bradykinesia motor tasks. Several features were extracted from the audio signal, including number of taps, speed, sound intensity, decrement and freezes. For each motor task, two supervised machine learning models were trained, Logistic Regression (LR) and Support Vector Machine (SVM). RESULTS: Both classifiers were able to separate patients from controls reasonably well for the leg agility task, area under the receiver operating characteristic curve (AUC): 0.92 (95%CI: 0.78-0.99) for LR and 0.93 (0.81-1.00) for SVM. Also, models were able to differentiate less severe bradykinesia from severe bradykinesia, particularly for the pronation-supination motor task, with AUC: 0.90 (0.62-1.00) for LR and 0.82 (0.45-0.97) for SVM. CONCLUSION: This audio-based approach discriminates PD from healthy controls with moderate-high accuracy and separated individuals with less severe bradykinesia from those with severe bradykinesia. Sound analysis may contribute to the identification and monitoring of bradykinesia.

Novel compound heterozygous ATP1A2 variants in a patient with fetal akinesia/hypokinesia sequence.

ATP1A2 encodes a subunit of sodium/potassium-transporting adenosine triphosphatase (Na+ /K+ -ATPase). Heterozygous pathogenic variants of ATP1A2 cause familial hemiplegic migraine, alternating hemiplegia of childhood, and developmental and epileptic encephalopathy. Biallelic loss-of-function variants in ATP1A2 lead to fetal akinesia, respiratory insufficiency, microcephaly, polymicrogyria, and dysmorphic facies, resulting in fetal death. Here, we describe a patient with compound heterozygous ATP1A2 variants consisting of missense and nonsense variants. He survived after birth with brain malformations and the fetal akinesia/hypokinesia sequence. We report a novel type of compound heterozygous variant that might extend the disease spectrum of ATP1A2.

Motivational Vigor in Parkinson's Disease Requires the Short and Long Duration Response to Levodopa.

BACKGROUND: Impaired movement vigor (bradykinesia) is a cardinal feature of Parkinson's disease (PD) and hypothesized to result from abnormal motivational processes-impaired motivation-vigor coupling. Dopamine replacement therapy (DRT) improves bradykinesia, but the response to DRT is multifaceted, comprising a short-duration response (SDR) and a long-duration response (LDR) only manifesting with chronic treatment. Prior experiments assessing motivation-vigor coupling in PD used chronically treated subjects, obscuring the roles of the SDR and LDR. METHODS: To disambiguate the SDR and LDR, 11 de novo PD subjects (6 male [M]:5 female [F]; mean age, 67) were studied before treatment, after an acute levodopa (l-dopa) dose, and in both the practical "off" (LDR) and "on" (LDR + SDR) states after chronic stable treatment. At each visit, subjects were characterized with a standard battery including the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and an incentivized joystick task to assess motor performance in response to varying rewards. RESULTS: l-Dopa induced a robust SDR and LDR, with further improvement in the combined SDR + LDR state. At baseline, after acute treatment (SDR), and after LDR induction, subjects did not exhibit the normal increase in movement speed with increasing reward. Only in the combined SDR + LDR state was there restoration of motivation-vigor coupling. CONCLUSIONS: Although consistent with prior results in chronically treated PD subjects, the significant improvement in motor performance observed with the SDR and LDR suggests that bradykinesia is not solely secondary to deficient modulation of motivational processes. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Locomotor Behavior and Memory Dysfunction Induced by 3-Nitropropionic Acid in Adult Zebrafish: Modulation of Dopaminergic Signaling.

Huntington's disease (HD) is a progressive neurodegenerative disease characterized by neuropsychiatric disturbance, cognitive impairment, and locomotor dysfunction. In the early stage (chorea) of HD, expression of dopamine D2 receptors (D2R) is reduced, whereas dopamine (DA) levels are increased. Contrary, in the late stage (bradykinesia), DA levels and the expression of D2R and dopamine D1 receptors (D1R) are reduced. 3-Nitropropionic acid (3-NPA) is a toxin that may replicate HD behavioral phenotypes and biochemical aspects. This study assessed the neurotransmitter levels, dopamine receptor gene expression, and the effect of acute exposure to quinpirole (D2R agonist) and eticlopride (D2R antagonist) in an HD model induced by 3-NPA in adult zebrafish. Quinpirole and eticlopride were acutely applied by i.p. injection in adult zebrafish after chronic treatment of 3-NPA (60 mg/kg). 3-NPA treatment caused a reduction in DA, glutamate, and serotonin levels. Quinpirole reversed the bradykinesia and memory loss induced by 3-NPA. Together, these data showed that 3-NPA acts on the dopaminergic system and causes biochemical alterations similar to late-stage HD. These data reinforce the hypothesis that DA levels are linked with locomotor and memory deficits. Thus, these findings may suggest that the use of DA agonists could be a pharmacological strategy to improve the bradykinesia and memory deficits in the late-stage HD.

Ucp4 Knockdown of Cerebellar Purkinje Cells Induces Bradykinesia.

Although uncoupling protein 4 (UCP4) is the most abundant protein reported in the brain, the biological function of UCP4 in cerebellum and pathological outcome of UCP4 deficiency in cerebellum remain obscure. To evaluate the role of Ucp4 in the cerebellar Purkinje cells (PCs), we generated the conditional knockdown of Ucp4 in PCs (Pcp2cre;Ucp4fl/fl mice) by breeding Ucp4fl/fl mice with Pcp2cre mice. Series results by Western blot, immunofluorescent staining, and triple RNAscope in situ hybridization confirmed the specific ablation of Ucp4 in PCs in Pcp2cre;Ucp4fl/fl mice, but did not affect the expression of Ucp2, the analog of Ucp4. Combined behavioral tests showed that Pcp2cre;Ucp4fl/fl mice displayed a characteristic bradykinesia in the spontaneous movements. The electromyogram recordings detection excluded the possibility of hypotonia in Pcp2cre;Ucp4fl/fl mice. And the electrical patch clamp recordings showed the altered properties of PCs in Pcp2cre;Ucp4fl/fl mice. Moreover, transmission electron microscope (TEM) results showed the increased mitochondrial circularity in PCs; ROS probe imaging showed the increased ROS generation in molecular layer; and finally, microplate reader assay showed the significant changes of mitochondrial functions, including ROS, ATP, and MMP in the isolated cerebellum tissue. The results suggested that the specific knockdown of mitochondrial protein Ucp4 could damage PCs possibly by attacking their mitochondrial function. The present study is the first to report a close relationship between UCP4 deletion with PCs impairment, and suggests the importance of UCP4 in the substantial support of mitochondrial function homeostasis in bradykinesia. UCP4 might be a therapeutic target for the cerebellar-related movement disorder.

Clinical severity in Parkinson's disease is determined by decline in cortical compensation.

Dopaminergic dysfunction in the basal ganglia, particularly in the posterior putamen, is often viewed as the primary pathological mechanism behind motor slowing (i.e. bradykinesia) in Parkinson's disease. However, striatal dopamine loss fails to account for interindividual differences in motor phenotype and rate of decline, implying that the expression of motor symptoms depends on additional mechanisms, some of which may be compensatory in nature. Building on observations of increased motor-related activity in the parieto-premotor cortex of Parkinson patients, we tested the hypothesis that interindividual differences in clinical severity are determined by compensatory cortical mechanisms and not just by basal ganglia dysfunction. Using functional MRI, we measured variability in motor- and selection-related brain activity during a visuomotor task in 353 patients with Parkinson's disease (≤5 years disease duration) and 60 healthy controls. In this task, we manipulated action selection demand by varying the number of possible actions that individuals could choose from. Clinical variability was characterized in two ways. First, patients were categorized into three previously validated, discrete clinical subtypes that are hypothesized to reflect distinct routes of α-synuclein propagation: diffuse-malignant (n = 42), intermediate (n = 128) or mild motor-predominant (n = 150). Second, we used the scores of bradykinesia severity and cognitive performance across the entire sample as continuous measures. Patients showed motor slowing (longer response times) and reduced motor-related activity in the basal ganglia compared with controls. However, basal ganglia activity did not differ between clinical subtypes and was not associated with clinical scores. This indicates a limited role for striatal dysfunction in shaping interindividual differences in clinical severity. Consistent with our hypothesis, we observed enhanced action selection-related activity in the parieto-premotor cortex of patients with a mild-motor predominant subtype, both compared to patients with a diffuse-malignant subtype and controls. Furthermore, increased parieto-premotor activity was related to lower bradykinesia severity and better cognitive performance, which points to a compensatory role. We conclude that parieto-premotor compensation, rather than basal ganglia dysfunction, shapes interindividual variability in symptom severity in Parkinson's disease. Future interventions may focus on maintaining and enhancing compensatory cortical mechanisms, rather than only attempting to normalize basal ganglia dysfunction.

A pilot study for testing a low-cost 3D design with an inertial sensor for the quantitative assessment of finger tapping in patients with Parkinson's Disease.

Parkinson's disease (PD) is one of the most common neurodegenerative disorders worldwide. Current identification and monitoring of its motor symptoms depends on the clinical expertise. Repetitive finger tapping is one of the most common clinical maneuvers to assess for bradykinesia. Despite the increasing use of technology aids to quantitatively characterize the motor symptoms of PD, there is still a relative lack of clinical evidence to support their widespread use, particularly in low-resource settings. In this pilot study, we used a low-cost design prototype coupled with an inertial sensor is coupled to quantify the frequency of the finger tapping movements in four participants with PD. Repetitive finger tapping was performed using both hands before and after taking levodopa as part of their clinical treatment. The proposed 3D design allowed repetitive movements to be performed without issues. The maximum frequency of finger tapping was in the range of 0.1 to 4.3 Hz. Levodopa was associated with variable changes in the maximum frequency of finger tapping. This pilot study shows the feasibility for low-cost technology to quantitatively characterize repetitive movements in people living with PD.Clinical relevance- In this pilot study, a low-cost inertial sensor coupled to a design prototype was feasible to characterize the frequency of repetitive finger tapping movements in four participants with PD. This method could be used to quantitatively identify and monitor bradykinesia in people living with PD.

A Deep Learning Approach for Grading of Motor Impairment Severity in Parkinson's Disease.

Objective and quantitative monitoring of movement impairments is crucial for detecting progression in neurological conditions such as Parkinson's disease (PD). This study examined the ability of deep learning approaches to grade motor impairment severity in a modified version of the Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) using low-cost wearable sensors. A convolutional neural network architecture, XceptionTime, was used to classify lower and higher levels of motor impairment in persons with PD, across five distinct rhythmic tasks: finger tapping, hand movements, pronation-supination movements of the hands, toe tapping, and leg agility. In addition, an aggregate model was trained on data from all tasks together for evaluating bradykinesia symptom severity in PD. The model performance was highest in the hand movement tasks with an accuracy of 82.6% in the hold-out test dataset; the accuracy for the aggregate model was 79.7%, however, it demonstrated the lowest variability. Overall, these findings suggest the feasibility of integrating low-cost wearable technology and deep learning approaches to automatically and objectively quantify motor impairment in persons with PD. This approach may provide a viable solution for a widely deployable telemedicine solution.

[The efficacy analysis of neurosurgical robot-assisted DBS in the treatment of elderly Parkinson's disease].

Objective: To investigate the surgical efficacy of neurosurgery robot deep brain stimulation(DBS) in the treatment of elderly Parkinson's disease(PD). Methods: The clinical data of elderly patients (≥75 years) with PD who underwent neurosurgical robot-assisted DBS surgery in the Department of Neurosurgery of the General Hospital of Northern Theater Command from September 2016 to September 2022 were collected retrospectively. Operation time, electrode implantation duration, postoperative pneumocephalus volume, electrode implantation accuracy, the Tao's DBS surgery scale, perioperative complications were analyzed.The unified Parkinson's disease rating scales (UPDRS), UPDRS-Ⅲ, tremor, rigidity, bradykinesia, axial, Barthel Activities of Daily Living (ADL-Barthel), Levodopa Equivalent Daily Dose (LEDD), Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD) scores and mortality were assessed respectively before operation, 6, 12 and 24 months after operation and last follow-up. Results: A total of 25 elderly patients were enrolled, including 14 males and 11 females, aged(78.3±3.2) years. Nine patients had underlying diseases. Nine patients (36%) underwent bilateral Globus Pallidus pars Interna deep brain stimulation (GPi-DBS) and 16 patients (64%) underwent bilateral subthalamic nucleus deep brain stimulation (STN-DBS).The operation time was (1.56±0.19) hours, the electrode implantation duration was (1.01±0.19) hours, the pneumocephalus volume was 9.8(4.7, 23.3) cm3, and the electrode implantation accuracy was (0.84±0.24) mm, the Tao's DBS surgery scale was (80.2±6.2).The follow-up time [M(Q1, Q3)] was 57.3(27.9, 75.7) months. No serious complications such as intracranial hemorrhage, infection or poor wound healing occurred during the perioperative period. The improvement rate of UPDRS, UPDRS-Ⅲ, rigidity, bradykinesia, and LEDD at 6 months after surgery was significantly higher than that at 24 months after surgery and at the last follow-up (all P<0.05); the improvement rate of axial symptoms, ADL-Barthel score, and MoCA score at 6 months after surgery was significantly higher than that at the last follow-up (P<0.05). HAMD and HAMA scores showed no significant improvement during follow-up after surgery (both P>0.05). At the last follow-up, 12 patients died, with death time of (35.1±20.2) months after operation, and the death age of [M(Q1, Q3)] 80(79, 83)years. Conclusions: Robot-assisted DBS surgery for elderly patients with PD is accurate and safe, and the postoperative symptoms are significantly improved, and they can benefit from neuromodulation for long term, and the risks are controllable.

Development and implementation of the frog-in-maze game to study upper limb movement in people with Parkinson's disease.

Upper-limb bradykinesia occurs early in Parkinson's disease (PD) and bradykinesia is required for diagnosis. Our goal was to develop, implement and validate a game "walking" a frog through a maze using bimanual, alternating finger-tapping movements to provide a salient, objective, and remotely monitorable method of tracking disease progression and response to therapy in PD. Twenty-five people with PD and 16 people without PD participated. Responses on 5 different mazes were quantified and compared to spatiotemporal gait parameters and standard disease metrics in these participants. Intertap interval (ITI) on maze 2 & 3, which included turns, was strongly inversely related to stride-length and stride-velocity and directly related to motor UPDRS scores. Levodopa decreased ITI, except in maze 4. PD participants with freezing of gait had longer ITI on all mazes. The responses quantified on maze 2 & 3 were related to disease severity and gait stride-length, were levodopa responsive, and were worse in people with freezing of gait, suggesting that these mazes could be used to quantify motor dysfunction in PD. Programming our frog-in-maze game onto a remotely distributable platform could provide a tool to monitor disease progression and therapeutic response in people with PD, including during clinical trials.

Clinically Informed Automated Assessment of Finger Tapping Videos in Parkinson's Disease.

The utilization of Artificial Intelligence (AI) for assessing motor performance in Parkinson's Disease (PD) offers substantial potential, particularly if the results can be integrated into clinical decision-making processes. However, the precise quantification of PD symptoms remains a persistent challenge. The current standard Unified Parkinson's Disease Rating Scale (UPDRS) and its variations serve as the primary clinical tools for evaluating motor symptoms in PD, but are time-intensive and prone to inter-rater variability. Recent work has applied data-driven machine learning techniques to analyze videos of PD patients performing motor tasks, such as finger tapping, a UPDRS task to assess bradykinesia. However, these methods often use abstract features that are not closely related to clinical experience. In this paper, we introduce a customized machine learning approach for the automated scoring of UPDRS bradykinesia using single-view RGB videos of finger tapping, based on the extraction of detailed features that rigorously conform to the established UPDRS guidelines. We applied the method to 75 videos from 50 PD patients collected in both a laboratory and a realistic clinic environment. The classification performance agreed well with expert assessors, and the features selected by the Decision Tree aligned with clinical knowledge. Our proposed framework was designed to remain relevant amid ongoing patient recruitment and technological progress. The proposed approach incorporates features that closely resonate with clinical reasoning and shows promise for clinical implementation in the foreseeable future.