A Transferable Lidar-Based Method to Conduct Contactless Assessments of Gait Parameters in Diverse Home-like Environments.

Gait abnormalities in older adults are linked to increased risks of falls, institutionalization, and mortality, necessitating accurate and frequent gait assessments beyond traditional clinical settings. Current methods, such as pressure-sensitive walkways, often lack the continuous natural environment monitoring needed to understand an individual's gait fully during their daily activities. To address this gap, we present a Lidar-based method capable of unobtrusively and continuously tracking human leg movements in diverse home-like environments, aiming to match the accuracy of a clinical reference measurement system. We developed a calibration-free step extraction algorithm based on mathematical morphology to realize Lidar-based gait analysis. Clinical gait parameters of 45 healthy individuals were measured using Lidar and reference systems (a pressure-sensitive walkway and a video recording system). Each participant participated in three predefined ambulation experiments by walking over the walkway. We observed linear relationships with strong positive correlations (R2>0.9) between the values of the gait parameters (step and stride length, step and stride time, cadence, and velocity) measured with the Lidar sensors and the pressure-sensitive walkway reference system. Moreover, the lower and upper 95% confidence intervals of all gait parameters were tight. The proposed algorithm can accurately derive gait parameters from Lidar data captured in home-like environments, with a performance not significantly less accurate than clinical reference systems.

Prognosis of impulse control disorders in Parkinson's disease: a prospective controlled study.

BACKGROUND: The long-term prognosis of impulsive compulsive disorders (ICD) remains poorly studied in Parkinson's disease (PD). OBJECTIVE: Evaluating the natural history of ICD and its impact on PD symptoms including cognition and treatment adjustments. MATERIALS AND METHODS: We assessed PD patients at baseline (BL) with (BL-ICD+) or without (BL-ICD-) ICD despite dopamine agonist (DA) exposure of > 300 mg levodopa-equivalent daily dose for > 12 months at baseline and after more than two years of follow-up. ICD were assessed using the Ardouin's Scale of Behaviors in PD (ASBPD), cognition using the Mattis scale, and PD symptoms using the UPDRS score. Treatment adjustments, DA withdrawal-associated symptoms, and ICDs social consequences were recorded. RESULTS: 149 patients were included (78 cases and 71 controls), mean duration of follow-up was 4.4 ± 1 years. At baseline, psychiatric disorders were more common among BL-ICD + (42.3 vs 12.3% among BL-ICD-, p < 0.01). At follow-up, 53.8% of BL-ICD + were not ICD-free while 21.1% of BL-ICD- had developed ICD. BL-ICD + more frequently experienced akinesia (21.8 vs 8.5%, p = 0.043) and rigidity worsening (11.5 vs 1.4%, p = 0.019) following therapeutic modifications. Decision to decrease > 50% DA doses (12.8 vs 1.4%, p = 0.019) or to withdraw DA (19.2 vs 5.6%, p = 0.025) was more frequently considered among BL-ICD+ . At follow-up, the prevalence of cognitive decline was lower among BL-ICD + (19.2 vs 37.1%, p = 0.025). CONCLUSION: ICDs were associated with increased psychiatric burden at baseline and better cognitive prognosis. Most patients were still showing ICDs at the follow-up visit, suggesting ICD to be considered as a chronic, neuropsychiatric disorder.

Management of Impulse Control and Related Disorders in Parkinson's Disease: An Expert Consensus.

BACKGROUND: Impulse-control and related behavioral disorders (ICBDs) significantly impact the lives of Parkinson's disease (PD) patients and caregivers, with lasting consequences if undiagnosed and untreated. While ICBD pathophysiology and risk factors are well-studied, a standardized severity definition and treatment evidence remain elusive. OBJECTIVE: This work aimed to establish international expert consensus on ICBD treatment strategies. To comprehensively address diverse treatment availabilities, experts from various continents were included. METHODS: From 2021 to 2023, global movement disorders specialists engaged in a Delphi process. A core expert group initiated surveys, involving a larger panel in three iterations, leading to refined severity definitions and treatment pathways. RESULTS: Experts achieved consensus on defining ICBD severity, emphasizing regular PD patient screenings for early detection. General treatment recommendations focused on continuous monitoring, collaboration with significant others, and seeking specialist advice for legal or financial challenges. For mild to severe ICBDs, gradual reduction in dopamine agonists was endorsed, followed by reductions in other PD medications. Second-line treatment strategies included diverse approaches like reversing the last medication change, cognitive behavior therapy, subthalamic nucleus deep brain stimulation, and specific medications like quetiapine, clozapine, and antidepressants. The panel reached consensus on distinct treatment pathways for punding and dopamine dysregulation syndrome, formulating therapy recommendations. Comprehensive discussions addressed management strategies for the exacerbation of either motor or non-motor symptoms following the proposed treatments. CONCLUSION: The consensus offers in-depth insights into ICBD management, presenting clear severity criteria and expert consensus treatment recommendations. The study highlights the critical need for further research to enhance ICBD management. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Subthalamic stimulation has acute psychotropic effects and improves neuropsychiatric fluctuations in Parkinson's disease.

Background: Subthalamic nucleus deep brain stimulation (STN-DBS) is a well-established treatment for motor complications in Parkinson's disease (PD). However, its effects on neuropsychiatric symptoms remain disputed. The aim of this study was to evaluate the effects of STN-DBS on neuropsychiatric symptoms in PD. Methods: We retrospectively assessed 26 patients with PD who underwent a preoperative levodopa challenge and postoperative levodopa and stimulation challenges 1 year after STN-DBS. Based on the Neuropsychiatric Fluctuations Scale, Neuropsychiatric State Scores and Neuropsychiatric Fluctuation Indices (NFIs) were calculated. Mixed-effects models with random effects for intercept were used to examine the association of Neuropsychiatric State Score and NFI with the different assessment conditions. Results: In acute challenge conditions, there was an estimated increase of 15.9 points in the Neuropsychiatric State Score in stimulation ON conditions (95% CI 11.4 to 20.6, p<0.001) and 7.6 points in medication ON conditions (95% CI 3.3 to 11.9, p<0.001). Neuropsychiatric fluctuations induced by levodopa, quantified with NFI, decreased by 35.54% (95% CI 49.3 to 21.8, p<0.001) 1 year after STN-DBS. Conclusions: Bilateral STN-DBS at therapeutic parameters has acute psychotropic effects similar to levodopa and can modulate and decrease levodopa-induced neuropsychiatric fluctuations.

Electroencephalographic Abnormalities in a Patient Suffering from Long-Term Neuropsychological Complications following SARS-CoV-2 Infection.

Introduction: Emotional apathy has recently been identified as a common symptom of long COVID. While recent meta-analyses have demonstrated generalized EEG slowing with the emergence of delta rhythms in patients hospitalized for severe SARS-CoV-2 infection, no EEG study or dopamine transporter scintigraphy (DaTSCAN) has been performed in patients with long COVID presenting with apathy. The objective of this case report was to explore the pathophysiology of neuropsychological symptoms in long COVID. Case Presentation: A 47-year-old patient who developed a long COVID with prominent apathy following an initially clinically mild SARS-CoV-2 infection underwent neuropsychological assessment, cerebral MRI, DaTSCAN, and resting-state high-density EEG 7 months after SARS-CoV-2 infection. The EEG data were compared to those of 21 healthy participants. The patient presented with apathy, cognitive difficulties with dysexecutive syndrome, moderate attentional and verbal episodic memory disturbances, and resolution of premorbid mild gaming disorder, mild mood disturbances, and sleep disturbances. His MRI and DaTSCAN were unremarkable. EEG revealed a complex pattern of oscillatory abnormalities compared to the control group, with a strong increase in whole-scalp delta and beta band activity, as well as a decrease in alpha band activity. Overall, these effects were more prominent in the frontal-central-temporal region. Conclusion: These results suggest widespread changes in EEG oscillatory patterns in a patient with long COVID characterized by neuropsychological complications with prominent apathy. Despite the inherent limitations of a case report, these results suggest dysfunction in the cortical networks involved in motivation and emotion.

Role of sleep in neurodegeneration: the consensus report of the 5th Think Tank World Sleep Forum.

Sleep abnormalities may represent an independent risk factor for neurodegeneration. An international expert group convened in 2021 to discuss the state-of-the-science in this domain. The present article summarizes the presentations and discussions concerning the importance of a strategy for studying sleep- and circadian-related interventions for early detection and prevention of neurodegenerative diseases. An international expert group considered the current state of knowledge based on the most relevant publications in the previous 5 years; discussed the current challenges in the field of relationships among sleep, sleep disorders, and neurodegeneration; and identified future priorities. Sleep efficiency and slow wave activity during non-rapid eye movement (NREM) sleep are decreased in cognitively normal middle-aged and older adults with Alzheimer's disease (AD) pathology. Sleep deprivation increases amyloid-ß (Aß) concentrations in the interstitial fluid of experimental animal models and in cerebrospinal fluid in humans, while increased sleep decreases Aß. Obstructive sleep apnea (OSA) is a risk factor for dementia. Studies indicate that positive airway pressure (PAP) treatment should be started in patients with mild cognitive impairment or AD and comorbid OSA. Identification of other measures of nocturnal hypoxia and sleep fragmentation could better clarify the role of OSA as a risk factor for neurodegeneration. Concerning REM sleep behavior disorder (RBD), it will be crucial to identify the subset of RBD patients who will convert to a specific neurodegenerative disorder. Circadian sleep-wake rhythm disorders (CSWRD) are strong predictors of caregiver stress and institutionalization, but the absence of recommendations or consensus statements must be considered. Future priorities include to develop and validate existing and novel comprehensive assessments of CSWRD in patients with/at risk for dementia. Strategies for studying sleep-circadian-related interventions for early detection/prevention of neurodegenerative diseases are required. CSWRD evaluation may help to identify additional biomarkers for phenotyping and personalizing treatment of neurodegeneration.

Imbalanced motivated behaviors according to motor sign asymmetry in drug-naïve Parkinson's disease.

Few studies have considered the influence of motor sign asymmetry on motivated behaviors in de novo drug-naïve Parkinson's disease (PD). We tested whether motor sign asymmetry could be associated with different motivated behavior patterns in de novo drug-naïve PD. We performed a cross-sectional study in 128 de novo drug-naïve PD patients and used the Ardouin Scale of Behavior in Parkinson's disease (ASBPD) to assess a set of motivated behaviors. We assessed motor asymmetry based on (i) side of motor onset and (ii) MDS-UPDRS motor score, then we compared right hemibody Parkinson's disease to left hemibody Parkinson's disease. According to the MDS-UPDRS motor score, patients with de novo right hemibody PD had significantly lower frequency of approach behaviors (p = 0.031), including nocturnal hyperactivity (p = 0.040), eating behavior (p = 0.040), creativity (p = 0.040), and excess of motivation (p = 0.017) than patients with de novo left hemibody PD. Patients with de novo left hemibody PD did not significantly differ from those with de novo right hemibody PD regarding avoidance behaviors including apathy, anxiety and depression. Our findings suggest that motor sign asymmetry may be associated with an imbalance between motivated behaviors in de novo drug-naïve Parkinson's disease.

Correction: Association of Rare Genetic Variants in Opioid Receptors with Tourette Syndrome.

[This corrects the article DOI: 10.5334/tohm.464.].

Programming of subthalamic nucleus deep brain stimulation with hyperdirect pathway and corticospinal tract-guided parameter suggestions.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for advanced Parkinson's disease. Stimulation of the hyperdirect pathway (HDP) may mediate the beneficial effects, whereas stimulation of the corticospinal tract (CST) mediates capsular side effects. The study's objective was to suggest stimulation parameters based on the activation of the HDP and CST. This retrospective study included 20 Parkinson's disease patients with bilateral STN DBS. Patient-specific whole-brain probabilistic tractography was performed to extract the HDP and CST. Stimulation parameters from monopolar reviews were used to estimate volumes of tissue activated and to determine the streamlines of the pathways inside these volumes. The activated streamlines were related to the clinical observations. Two models were computed, one for the HDP to estimate effect thresholds and one for the CST to estimate capsular side effect thresholds. In a leave-one-subject-out cross-validation, the models were used to suggest stimulation parameters. The models indicated an activation of 50% of the HDP at effect threshold, and 4% of the CST at capsular side effect threshold. The suggestions for best and worst levels were significantly better than random suggestions. Finally, we compared the suggested stimulation thresholds with those from the monopolar reviews. The median suggestion errors for the effect threshold and side effect threshold were 1 and 1.5 mA, respectively. Our stimulation models of the HDP and CST suggested STN DBS settings. Prospective clinical studies are warranted to optimize tract-guided DBS programming. Together with other modalities, these may allow for assisted STN DBS programming.

Spectral Topography of the Subthalamic Nucleus to Inform Next-Generation Deep Brain Stimulation.

BACKGROUND: The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing-based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN). OBJECTIVES: The aims were to systematically investigate the spectral topography, including a wide range of sub-bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS. METHODS: STN-LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub-bands (delta, theta, alpha, low-beta, high-beta, low-gamma, high-gamma, and fast-gamma (FG) as well as low- and fast high-frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS. RESULTS: The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior-superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub-bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher-frequency hot spots were predictive for the best rigidity response to DBS. CONCLUSIONS: The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next-generation sensing-based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Deep Brain Stimulation: When to Test Directional?

Background: Directional deep brain stimulation (DBS) allows for steering of the stimulation field, but extensive and time-consuming testing of all segmented contacts is necessary to identify the possible benefit of steering. It is therefore important to determine under which circumstances directional current steering is advantageous. Methods: Fifty two Parkinson's disease patients implanted in the STN with a directional DBS system underwent a standardized monopolar programming session 5 to 9 months after implantation. Individual contacts were tested for a potential advantage of directional stimulation. Results were used to build a prediction model for the selection of ring levels that would benefit from directional stimulation. Results: On average, there was no significant difference in therapeutic window between ring-level contact and best directional contact. However, according to our standardized protocol, 35% of the contacts and 66% of patients had a larger therapeutic window under directional stimulation compared to ring-mode. The segmented contacts warranting directional current steering could be predicted with a sensitivity of 79% and a specificity of 57%. Conclusion: To reduce time required for DBS programming, we recommend additional directional contact testing initially only on ring-level contacts with a therapeutic window of less than 2.0 mA.

An Overview of Wearable Haptic Technologies and Their Performance in Virtual Object Exploration.

We often interact with our environment through manual handling of objects and exploration of their properties. Object properties (OP), such as texture, stiffness, size, shape, temperature, weight, and orientation provide necessary information to successfully perform interactions. The human haptic perception system plays a key role in this. As virtual reality (VR) has been a growing field of interest with many applications, adding haptic feedback to virtual experiences is another step towards more realistic virtual interactions. However, integrating haptics in a realistic manner, requires complex technological solutions and actual user-testing in virtual environments (VEs) for verification. This review provides a comprehensive overview of recent wearable haptic devices (HDs) categorized by the OP exploration for which they have been verified in a VE. We found 13 studies which specifically addressed user-testing of wearable HDs in healthy subjects. We map and discuss the different technological solutions for different OP exploration which are useful for the design of future haptic object interactions in VR, and provide future recommendations.

Development of an Open-source and Lightweight Sensor Recording Software System for Conducting Biomedical Research: Technical Report.

BACKGROUND: Digital sensing devices have become an increasingly important component of modern biomedical research, as they help provide objective insights into individuals' everyday behavior in terms of changes in motor and nonmotor symptoms. However, there are significant barriers to the adoption of sensor-enhanced biomedical solutions in terms of both technical expertise and associated costs. The currently available solutions neither allow easy integration of custom sensing devices nor offer a practicable methodology in cases of limited resources. This has become particularly relevant, given the need for real-time sensor data that could help lower health care costs by reducing the frequency of clinical assessments performed by specialists and improve access to health assessments (eg, for people living in remote areas or older adults living at home). OBJECTIVE: The objective of this paper is to detail the end-to-end development of a novel sensor recording software system that supports the integration of heterogeneous sensor technologies, runs as an on-demand service on consumer-grade hardware to build sensor systems, and can be easily used to reliably record longitudinal sensor measurements in research settings. METHODS: The proposed software system is based on a server-client architecture, consisting of multiple self-contained microservices that communicated with each other (eg, the web server transfers data to a database instance) and were implemented as Docker containers. The design of the software is based on state-of-the-art open-source technologies (eg, Node.js or MongoDB), which fulfill nonfunctional requirements and reduce associated costs. A series of programs to facilitate the use of the software were documented. To demonstrate performance, the software was tested in 3 studies (2 gait studies and 1 behavioral study assessing activities of daily living) that ran between 2 and 225 days, with a total of 114 participants. We used descriptive statistics to evaluate longitudinal measurements for reliability, error rates, throughput rates, latency, and usability (with the System Usability Scale [SUS] and the Post-Study System Usability Questionnaire [PSSUQ]). RESULTS: Three qualitative features (event annotation program, sample delay analysis program, and monitoring dashboard) were elaborated and realized as integrated programs. Our quantitative findings demonstrate that the system operates reliably on consumer-grade hardware, even across multiple months (>420 days), providing high throughput (2000 requests per second) with a low latency and error rate (<0.002%). In addition, the results of the usability tests indicate that the system is effective, efficient, and satisfactory to use (mean usability ratings for the SUS and PSSUQ were 89.5 and 1.62, respectively). CONCLUSIONS: Overall, this sensor recording software could be leveraged to test sensor devices, as well as to develop and validate algorithms that are able to extract digital measures (eg, gait parameters or actigraphy). The proposed software could help significantly reduce barriers related to sensor-enhanced biomedical research and allow researchers to focus on the research questions at hand rather than on developing recording technologies.

Results of a Randomized Clinical Trial of Speech After Early Neurostimulation in Parkinson's Disease.

BACKGROUND: The EARLYSTIM trial demonstrated for Parkinson's disease patients with early motor complications that deep brain stimulation of the subthalamic nucleus (STN-DBS) and best medical treatment (BMT) was superior to BMT alone. OBJECTIVE: This prospective, ancillary study on EARLYSTIM compared changes in blinded speech intelligibility assessment between STN-DBS and BMT over 2 years, and secondary outcomes included non-speech oral movements (maximum phonation time [MPT], oral diadochokinesis), physician- and patient-reported assessments. METHODS: STN-DBS (n = 102) and BMT (n = 99) groups underwent assessments on/off medication at baseline and 24 months (in four conditions: on/off medication, ON/OFF stimulation-for STN-DBS). Words and sentences were randomly presented to blinded listeners, and speech intelligibility rate was measured. Statistical analyses compared changes between the STN-DBS and BMT groups from baseline to 24 months. RESULTS: Over the 2-year period, changes in speech intelligibility and MPT, as well as patient-reported outcomes, were not different between groups, either off or on medication or OFF or ON stimulation, but most outcomes showed a nonsignificant trend toward worsening in both groups. Change in oral diadochokinesis was significantly different between STN-DBS and BMT groups, on medication and OFF STN-DBS, with patients in the STN-DBS group performing slightly worse than patients under BMT only. A signal for clinical worsening with STN-DBS was found for the individual speech item of the Unified Parkinson's Disease Rating Scale, Part III. CONCLUSION: At this early stage of the patients' disease, STN-DBS did not result in a consistent deterioration in blinded speech intelligibility assessment and patient-reported communication, as observed in studies of advanced Parkinson's Disease. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Probabilistic Subthalamic Nucleus Stimulation Sweet Spot Integration Into a Commercial Deep Brain Stimulation Programming Software Can Predict Effective Stimulation Parameters.

OBJECTIVES: Subthalamic nucleus (STN) deep brain stimulation (DBS) programming in patients with Parkinson disease (PD) may be challenging, especially when using segmented leads. In this study, we integrated a previously validated probabilistic STN sweet spot into a commercially available software to evaluate its predictive value for clinically effective DBS programming. MATERIALS AND METHODS: A total of 14 patients with PD undergoing bilateral STN DBS with segmented leads were included. A nonlinear co-registration of a previously defined probabilistic sweet spot onto the manually segmented STN was performed together with lead reconstruction and tractography of the corticospinal tract (CST) in each patient. Contacts were ranked (level and direction), and corresponding effect and side-effect thresholds were predicted based on the overlap of the volume of activated tissue (VTA) with the sweet spot and CST. Image-based findings were correlated with postoperative clinical testing results during monopolar contact review and chronic stimulation parameter settings used after 12 months. RESULTS: Image-based contact prediction showed high interrater reliability (Cohen kappa 0.851-0.91). Image-based and clinical ranking of the most efficient ring level and direction of stimulation were matched in 72% (95% CI 57.0-83.3) and 65% (95% CI 44.9-81.2), respectively, across the whole cohort. The mean difference between the predicted and clinically observed effect thresholds was 0.79 ± 0.69 mA (p = 0.72). The median difference between the predicted and clinically observed side-effect thresholds was -0.5 mA (p < 0.001, Wilcoxon paired signed rank test). CONCLUSIONS: Integration of a probabilistic STN functional sweet spot into a surgical programming software shows a promising capability to predict the best level and directional contact(s) as well as stimulation settings in DBS for PD and could be used to optimize programming with segmented lead technology. This integrated image-based programming approach still needs to be evaluated on a bigger data set and in a future prospective multicenter cohort.

Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease.

BACKGROUND: Deep brain stimulation (DBS) programming of multicontact DBS leads relies on a very time-consuming manual screening procedure, and strategies to speed up this process are needed. Beta activity in subthalamic nucleus (STN) local field potentials (LFP) has been suggested as a promising marker to index optimal stimulation contacts in patients with Parkinson disease. OBJECTIVE: In this study, we investigate the advantage of algorithmic selection and combination of multiple resting and movement state features from STN LFPs and imaging markers to predict three relevant clinical DBS parameters (clinical efficacy, therapeutic window, side-effect threshold). MATERIALS AND METHODS: STN LFPs were recorded at rest and during voluntary movements from multicontact DBS leads in 27 hemispheres. Resting- and movement-state features from multiple frequency bands (alpha, low beta, high beta, gamma, fast gamma, high frequency oscillations [HFO]) were used to predict the clinical outcome parameters. Subanalyses included an anatomical stimulation sweet spot as an additional feature. RESULTS: Both resting- and movement-state features contributed to the prediction, with resting (fast) gamma activity, resting/movement-modulated beta activity, and movement-modulated HFO being most predictive. With the proposed algorithm, the best stimulation contact for the three clinical outcome parameters can be identified with a probability of almost 90% after considering half of the DBS lead contacts, and it outperforms the use of beta activity as single marker. The combination of electrophysiological and imaging markers can further improve the prediction. CONCLUSION: LFP-guided DBS programming based on algorithmic selection and combination of multiple electrophysiological and imaging markers can be an efficient approach to improve the clinical routine and outcome of DBS patients.