Remote Evaluation of Sleep and Circadian Rhythms in Older Adults With Mild Cognitive Impairment and Dementia: Protocol for a Feasibility and Acceptability Mixed Methods Study.

BACKGROUND: Sleep disturbances are a potentially modifiable risk factor for neurodegenerative dementia secondary to Alzheimer disease (AD) and Lewy body disease (LBD). Therefore, we need to identify the best methods to study sleep in this population. OBJECTIVE: This study will assess the feasibility and acceptability of various wearable devices, smart devices, and remote study tasks in sleep and cognition research for people with AD and LBD. METHODS: We will deliver a feasibility and acceptability study alongside a prospective observational cohort study assessing sleep and cognition longitudinally in the home environment. Adults aged older than 50 years who were diagnosed with mild to moderate dementia or mild cognitive impairment (MCI) due to probable AD or LBD and age-matched controls will be eligible. Exclusion criteria include lack of capacity to consent to research, other causes of MCI or dementia, and clinically significant sleep disorders. Participants will complete a cognitive assessment and questionnaires with a researcher and receive training and instructions for at-home study tasks across 8 weeks. At-home study tasks include remote sleep assessments using wearable devices (electroencephalography headband and actigraphy watch), app-based sleep diaries, online cognitive assessments, and saliva samples for melatonin- and cortisol-derived circadian markers. Feasibility outcomes will be assessed relating to recruitment and retention, data completeness, data quality, and support required. Feedback on acceptability and usability will be collected throughout the study period and end-of-study interviews will be analyzed using thematic analysis. RESULTS: Recruitment started in February 2022. Data collection is ongoing, with final data expected in February 2024 and data analysis and publication of findings scheduled for the summer of 2024. CONCLUSIONS: This study will allow us to assess if remote testing using smart devices and wearable technology is a viable alternative to traditional sleep measurements, such as polysomnography and questionnaires, in older adults with and without MCI or dementia due to AD or LBD. Understanding participant experience and the barriers and facilitators to technology use for research purposes and remote research in this population will assist with the development of, recruitment to, and retention within future research projects studying sleep and cognition outside of the clinic or laboratory. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52652.

A multimodal dataset of real world mobility activities in Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterised by motor symptoms such as gait dysfunction and postural instability. Technological tools to continuously monitor outcomes could capture the hour-by-hour symptom fluctuations of PD. Development of such tools is hampered by the lack of labelled datasets from home settings. To this end, we propose REMAP (REal-world Mobility Activities in Parkinson's disease), a human rater-labelled dataset collected in a home-like setting. It includes people with and without PD doing sit-to-stand transitions and turns in gait. These discrete activities are captured from periods of free-living (unobserved, unstructured) and during clinical assessments. The PD participants withheld their dopaminergic medications for a time (causing increased symptoms), so their activities are labelled as being "on" or "off" medications. Accelerometry from wrist-worn wearables and skeleton pose video data is included. We present an open dataset, where the data is coarsened to reduce re-identifiability, and a controlled dataset available on application which contains more refined data. A use-case for the data to estimate sit-to-stand speed and duration is illustrated.

Remote evaluation of sleep to enhance understanding of early dementia due to Alzheimer's Disease (RESTED-AD): an observational cohort study protocol.

BACKGROUND: Sleep and circadian rhythm disorders are well recognised in both AD (Alzheimer's Disease) dementia and MCI-AD (Mild Cognitive Impairment due to Alzheimer's Disease). Such abnormalities include insomnia, excessive daytime sleepiness, decreased sleep efficiency, increased sleep fragmentation and sundowning. Enhancing understanding of sleep abnormalities may unveil targets for intervention in sleep, a promising approach given hypotheses that sleep disorders may exacerbate AD pathological progression and represent a contributory factor toward impaired cognitive performance and worse quality of life. This may also permit early diagnosis of AD pathology, widely acknowledged as a pre-requisite for future disease-modifying therapies. This study aims to bridge the divide between in-laboratory polysomnographic studies which allow for rich characterisation of sleep but in an unnatural setting, and naturalistic studies typically approximating sleep through use of non-EEG wearable devices. It is also designed to record sleep patterns over a 2 month duration sufficient to capture both infradian rhythm and compensatory responses following suboptimal sleep. Finally, it harnesses an extensively phenotyped population including with AD blood biomarkers. Its principal aims are to improve characterisation of sleep and biological rhythms in individuals with AD, particularly focusing on micro-architectural measures of sleep, compensatory responses to suboptimal sleep and the relationship between sleep parameters, biological rhythms and cognitive performance. METHODS/DESIGN: This observational cohort study has two arms (AD-MCI / mild AD dementia and aged-matched healthy adults). Each participant undergoes a baseline visit for collection of demographic, physiological and neuropsychological information utilising validated questionnaires. The main study period involves 7 nights of home-based multi-channel EEG sleep recording nested within an 8-week study period involving continuous wrist-worn actigraphy, sleep diaries and regular brief cognitive tests. Measurement of sleep parameters will be at home thereby obtaining a real-world, naturalistic dataset. Cognitive testing will be repeated at 6 months to stratify participants by longitudinal disease progression. DISCUSSION: This study will generate new insights particularly in micro-architectural measures of sleep, circadian patterns and compensatory sleep responses in a population with and without AD neurodegenerative change. It aims to enhance standards of remotely based sleep research through use of a well-phenotyped population and advanced sleep measurement technology.

Slower rates of prism adaptation but intact aftereffects in patients with early to mid-stage Parkinson's disease.

There is currently mixed evidence on the effect of Parkinson's disease on motor adaptation. Some studies report that patients display adaptation comparable to age-matched controls, while others report a complete inability to adapt to novel sensory perturbations. Here, early to mid-stage Parkinson's patients were recruited to perform a prism adaptation task. When compared to controls, patients showed slower rates of initial adaptation but intact aftereffects. These results support the suggestion that patients with early to mid-stage Parkinson's disease display intact adaptation driven by sensory prediction errors, as shown by the intact aftereffect. But impaired facilitation of performance through cognitive strategies informed by task error, as shown by the impaired initial adaptation. These results support recent studies that suggest that patients with Parkinson's disease retain the ability to perform visuomotor adaptation, but display altered use of cognitive strategies to aid performance and generalises these previous findings to the classical prism adaptation task.

Automated Real-World Video Analysis of Sit-to-Stand Transitions Predicts Parkinson's Disease Severity.

Introduction: Technology holds the potential to track disease progression and response to neuroprotective therapies in Parkinson's disease (PD). The sit-to-stand (STS) transition is a frequently occurring event which is important to people with PD. The aim of this study was to demonstrate an automatic approach to quantify STS duration and speed using a real-world free-living dataset and look at clinical correlations of the outcomes, including whether STS parameters change when someone withholds PD medications. Methods: Eighty-five hours of video data were collected from 24 participants staying in pairs for 5-day periods in a naturalistic setting. Skeleton joints were extracted from the video data; the head trajectory was estimated and used to estimate the STS parameters of duration and speed. Results: 3.14 STS transitions were seen per hour per person on average. Significant correlations were seen between automatic and manual STS duration (Pearson rho - 0.419, p = 0.042) and between automatic STS speed and manual STS duration (Pearson rho - 0.780, p < 0.001). Significant and strong correlations were seen between the gold-standard clinical rating scale scores and both STS duration and STS speed; these correlations were not seen in the STS transitions when the participants were carrying something in their hand(s). Significant differences were seen at the cohort level between control and PD participants' ON medications' STS duration (U = 6,263, p = 0.018) and speed (U = 9,965, p < 0.001). At an individual level, only two participants with PD became significantly slower to STS when they were OFF medications; withholding medications did not significantly change STS duration at an individual level in any participant. Conclusion: We demonstrate a novel approach to automatically quantify and ecologically validate two STS parameters which correlate with gold-standard clinical tools measuring disease severity in PD.

Inaccurate self-report of olfactory dysfunction in REM Sleep Behaviour Disorder and implications for prognosis.

Introduction: The earliest stages of alpha-synucleinopathies are accompanied by non-specific prodromal symptoms such as diminished sense of smell, constipation and depression, as well as more specific prodromal conditions including REM Sleep Behaviour Disorder (RBD). While the majority of RBD patients will develop an alpha-synucleinopathy, one of the greatest clinical challenges is determining whether and when individual patients will phenoconvert. Clinical evaluation of a patient presenting with RBD should therefore include robust and objective assessments of known alpha-synucleinopathy prodromes. Methods: This study compared olfactory function self-report measures with psychophysical 'Sniffin' Stick 16-item Identification' test scores in Control (n = 19), RBD (n = 16) and PD (n = 17) participants. Results: We confirm that olfactory test scores are significantly diminished in RBD and PD groups compared to Controls (p < 0.001, One-Way ANOVA with Tukey-Kramer Post-Hoc, effect size = 0.401). However, RBD participants were only 56 % accurate when self-reporting olfactory dysfunction, hence markedly less likely to perceive or acknowledge their own hyposmia compared to Controls (p = 0.045, Fisher's Exact Test, effect-size = 0.35). Conclusion: When isolated RBD presents with hyposmia, there is an increased likelihood of phenoconversion to Parkinson's Disease (PD) or Dementia with Lewy Bodies (DLB); unawareness of olfactory dysfunction in an individual with isolated RBD may therefore confound differential diagnosis and prognosis. Our results evidence the fallibility of olfactory function self-report in the context of RBD prognosis, indicating that clinical assessments of RBD patients should include more reliable measures of olfactory status.

Practically Defined Off-State Dyskinesia Following Repeated Intraputamenal Glial Cell Line-Derived Neurotrophic Factor Administration.

BACKGROUND: We recently showed that by employing an enhanced drug-delivery approach, repeated administration of glial cell line-derived neurotrophic factor (GDNF) can produce a spatially distributed increased 18 F-DOPA positron emission tomography (PET) uptake, suggesting sprouting of dopaminergic terminals throughout the putamen structure. Despite this, we failed to prove a significant measurable clinical response. Since, however, we have identified a subject demonstrating a temporal relationship between repeated GDNF infusions and dyskinesia arising in the practically defined off (pracoff) state. OBJECTIVES: To describe the development of pracoff dyskinesia across our study population and consider its utility as an indicator that trophic factor-induced terminal sprouting can affect enhanced endogenous dopamine levels. METHODS: This was a blinded retrospective analysis of videotaped motor assessments at eight weekly study visits. Dyskinesia in the pracoff and supramaximal on state were rated using the Clinical Dyskinesia Rating Scale. Logistic regression was employed to explore the predictors of pracoff dyskinesia. Generalized estimated equations were used to estimate the cumulative effect of repeated GDNF infusions. RESULTS: Mild-moderate choreiform dyskinesia in the pracoff state were seen in 47 assessments in 17 (n = 41) subjects. During the 18-month timeframe, each subsequent 8-week period of receiving GDNF increased the risk of demonstrating pracoff state dyskinesia by 34% (odds ratio [OR], 1.34 (95% confidence interval [CI], 1.20, 1.50); P < 0.001). An increasing supramaximal on dyskinesia score (OR, 1.17 [95% CI, 1.07, 1.30]; P = 0.001) also increased the likelihood of pracoff dyskinesia at that visit. CONCLUSIONS: We report the first description of increasingly prevalent pracoff-state dyskinesia developing during the course of a trophic factor study. This may provide a surrogate marker that GDNF can enable recovery of endogenous dopamine release even in advanced Parkinson's disease. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Understanding how people with Parkinson's disease turn in gait from a real-world in-home dataset.

INTRODUCTION: Turning in gait digital parameters may be useful in measuring disease progression in Parkinson's disease (PD), however challenges remain over algorithm validation in real-world settings. The influence of clinician observation on turning outcomes is poorly understood. Our objective is to describe a unique in-home video dataset and explore the use of turning parameters as biomarkers in PD. METHODS: 11 participants with PD, 11 control participants stayed in a home-like setting living freely for 5 days (with two sessions of clinical assessment), during which high-resolution video was captured. Clinicians watched the videos, identified turns and documented turning parameters. RESULTS: From 85 hours of video 3869 turns were evaluated, averaging at 22.7 turns per hour per person. 6 participants had significantly different numbers of turning steps and/or turn duration between "ON" and "OFF" medication states. Positive Spearman correlations were seen between the Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale III score with a) number of turning steps (rho = 0.893, p < 0.001), and b) duration of turn (rho = 0.744, p = 0.009) "OFF" medications. A positive correlation was seen "ON" medications between number of turning steps and clinical rating scale score (rho = 0.618, p = 0.048). Both cohorts took more steps and shorter durations of turn during observed clinical assessments than when free-living. CONCLUSION: This study shows proof of concept that real-world free-living turn duration and number of turning steps recorded can distinguish between PD medication states and correlate with gold-standard clinical rating scale scores. It illustrates a methodology for ecological validation of real-world digital outcomes.

Evaluation of Simvastatin as a Disease-Modifying Treatment for Patients With Parkinson Disease: A Randomized Clinical Trial.

Importance: Current treatments manage symptoms of Parkinson disease (PD), but no known treatment slows disease progression. Preclinical and epidemiological studies support the potential use of statins as disease-modifying therapy. Objective: To determine whether simvastatin has potential as a disease-modifying treatment for patients with moderate PD. Design, Setting, and Participants: This randomized clinical trial, a double-blind, parallel-group, placebo-controlled futility trial, was conducted between March 2016 and May 2020 within 23 National Health Service Trusts in England. Participants aged 40 to 90 years with a diagnosis of idiopathic PD, with a modified Hoehn and Yahr stage of 3.0 or less while taking medication, and taking dopaminergic medication with wearing-off phenomenon were included. Data were analyzed from May 2020 to September 2020, with additional analysis in February 2021. Interventions: Participants were allocated 1:1 to simvastatin or matched placebo via a computer-generated random sequence, stratified by site and Hoehn and Yahr stage. In the simvastatin arm, participants entered a 1-month phase of simvastatin, 40 mg daily, followed by 23 months of simvastatin, 80 mg daily, before a 2-month washout period. Main Outcomes and Measures: The prespecified primary outcome was 24-month change in Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UPDRS) part III score measured while not taking medication (high scores indicate worse outcome). The primary futility analysis included participants who commenced the 80-mg phase and had valid primary outcome data. The safety analysis included all participants who commenced trial treatment and is reported by dose at time of event. Results: Of 332 patients assessed for eligibility, 32 declined and 65 were ineligible. Of 235 recruited participants, 97 (41%) were female, 233 (99%) were White, and the mean (SD) age was 65.4 (9.4) years. A total of 216 patients progressed to the 80-mg dose. Primary outcome analysis (n = 178) indicated the simvastatin group had an additional deterioration in MDS-UPDRS III score while not taking medication at 24 months compared with the placebo group (1.52 points; 2-sided 80% CI, -0.77 to 3.80; 1-sided futility test P = .006). A total of 37 serious adverse events (AEs), including 3 deaths, and 171 AEs were reported for participants receiving 0-mg simvastatin; 37 serious AEs and 150 AEs were reported for participants taking 40 mg or 80 mg of simvastatin. Four participants withdrew from the trial because of an AE. Conclusions and Relevance: In this randomized clinical trial, simvastatin was futile as a disease-modifying therapy in patients with PD of moderate severity, providing no evidence to support proceeding to a phase 3 trial. Trial Registration: ISRCTN Identifier: 16108482.

Acceptability of an In-home Multimodal Sensor Platform for Parkinson Disease: Nonrandomized Qualitative Study.

BACKGROUND: Parkinson disease (PD) symptoms are complex, gradually progressive, and fluctuate hour by hour. Home-based technological sensors are being investigated to measure symptoms and track disease progression. A smart home sensor platform, with cameras and wearable devices, could be a useful tool to use to get a fuller picture of what someone's symptoms are like. High-resolution video can capture the ground truth of symptoms and activities. There is a paucity of information about the acceptability of such sensors in PD. OBJECTIVE: The primary objective of our study was to explore the acceptability of living with a multimodal sensor platform in a naturalistic setting in PD. Two subobjectives are to identify any suggested limitations and to explore the sensors' impact on participant behaviors. METHODS: A qualitative study was conducted with an inductive approach using semistructured interviews with a cohort of PD and control participants who lived freely for several days in a home-like environment while continuously being sensed. RESULTS: This study of 24 participants (12 with PD) found that it is broadly acceptable to use multimodal sensors including wrist-worn wearables, cameras, and other ambient sensors passively in free-living in PD. The sensor that was found to be the least acceptable was the wearable device. Suggested limitations on the platform for home deployment included camera-free time and space. Behavior changes were noted by the study participants, which may have related to being passively sensed. Recording high-resolution video in the home setting for limited periods of time was felt to be acceptable to all participants. CONCLUSIONS: The results broaden the knowledge of what types of sensors are acceptable for use in research in PD and what potential limitations on these sensors should be considered in future work. The participants' reported behavior change in this study should inform future similar research design to take this factor into account. Collaborative research study design, involving people living with PD at every stage, is important to ensure that the technology is acceptable and that the data outcomes produced are ecologically valid and accurate. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2020-041303.

An Automatic Gait Analysis Pipeline for Wearable Sensors: A Pilot Study in Parkinson's Disease.

The use of wearable sensors allows continuous recordings of physical activity from participants in free-living or at-home clinical studies. The large amount of data collected demands automatic analysis pipelines to extract gait parameters that can be used as clinical endpoints. We introduce a deep learning-based automatic pipeline for wearables that processes tri-axial accelerometry data and extracts gait events-bout segmentation, initial contact (IC), and final contact (FC)-from a single sensor located at either the lower back (near L5), shin or wrist. The gait events detected are posteriorly used for gait parameter estimation, such as step time, length, and symmetry. We report results from a leave-one-subject-out (LOSO) validation on a pilot study dataset of five participants clinically diagnosed with Parkinson's disease (PD) and six healthy controls (HC). Participants wore sensors at three body locations and walked on a pressure-sensing walkway to obtain reference gait data. Mean absolute errors (MAE) for the IC events ranged from 22.82 to 33.09 milliseconds (msecs) for the lower back sensor while for the shin and wrist sensors, MAE ranges were 28.56-64.66 and 40.19-72.50 msecs, respectively. For the FC-event detection, MAE ranges were 29.06-48.42, 40.19-72.70 and 36.06-60.18 msecs for the lumbar, wrist and shin sensors, respectively. Intraclass correlation coefficients, ICC(2,k), between the estimated parameters and the reference data resulted in good-to-excellent agreement (ICC ≥ 0.84) for the lumbar and shin sensors, excluding the double support time (ICC = 0.37 lumbar and 0.38 shin) and swing time (ICC = 0.55 lumbar and 0.59 shin). The wrist sensor also showed good agreements, but the ICCs were lower overall than for the other two sensors. Our proposed analysis pipeline has the potential to extract up to 100 gait-related parameters, and we expect our contribution will further support developments in the fields of wearable sensors, digital health, and remote monitoring in clinical trials.

Multimodal Classification of Parkinson's Disease in Home Environments with Resiliency to Missing Modalities.

Parkinson's disease (PD) is a chronic neurodegenerative condition that affects a patient's everyday life. Authors have proposed that a machine learning and sensor-based approach that continuously monitors patients in naturalistic settings can provide constant evaluation of PD and objectively analyse its progression. In this paper, we make progress toward such PD evaluation by presenting a multimodal deep learning approach for discriminating between people with PD and without PD. Specifically, our proposed architecture, named MCPD-Net, uses two data modalities, acquired from vision and accelerometer sensors in a home environment to train variational autoencoder (VAE) models. These are modality-specific VAEs that predict effective representations of human movements to be fused and given to a classification module. During our end-to-end training, we minimise the difference between the latent spaces corresponding to the two data modalities. This makes our method capable of dealing with missing modalities during inference. We show that our proposed multimodal method outperforms unimodal and other multimodal approaches by an average increase in F1-score of 0.25 and 0.09, respectively, on a data set with real patients. We also show that our method still outperforms other approaches by an average increase in F1-score of 0.17 when a modality is missing during inference, demonstrating the benefit of training on multiple modalities.

Per-oral image guided gastrojejunostomy insertion for levodopa-carbidopa intestinal gel in Parkinson's disease is safe and may be advantageous.

BACKGROUND: Procedural aspects and complications of gastrojejunostomy insertion are important considerations in the use of levodopa-carbidopa intestinal gel therapy (LCIG) and may limit uptake. We describe our experience of using per-oral image guided gastrojejunostomy (PIG-J) which avoids the need for endoscopy and routine sedation in percutaneous endoscopic gastrojejunostomy (PEG-J) and allows more secure tube placement than radiologically inserted gastrojejunostomy techniques. METHODS: We describe a case series of 32 patients undergoing PIG-J insertion for LCIG therapy in a single centre. Under local anaesthetic, a fluoroscopy-guided gastric puncture allows access for the guidewire which is then used to pull through the gastrostomy tube allowing for secure fixation, followed by placement of the gastrojejunal extension. RESULTS: Between December 2015 to April 2020, 32/34 patients referred for PIG-J underwent this procedure successfully, 2 cases unsuccessful due to technical considerations. One patient developed delirium following successful implantation. Ten patients (31%) required a replacement tube due to blockage or displacement within the first 12 months of placement, including 2 patients who needed more than one replacement. Minor complications occurred in 10 other patients (31%), including infection (9 patients); a small haematoma not requiring intervention who later developed an infection (1 patient); and peri-stomal acid leakage (1 patient). CONCLUSION: In summary, PIG-J insertion is safe with a similar complication rate to traditional PEG-J, well tolerated and effective for use in LCIG administration. This may widen access to LCIG for PD patients who may not be suitable or unable to tolerate PEG-J.

The Association Between Frailty and Parkinson's Disease in the ReSPOnD Trial.

BACKGROUND: Frailty and Parkinson's disease (PD) are both highly prevalent in older people, but few studies have studied frailty in people with Parkinson's. Identifying frailty in this population is vital, to target new interventions to those who would most benefit. METHODS: Data were collected as part of the double-blind randomised controlled rivastigmine to stabilise gait ReSPonD trial in 130 people with Hoehn and Yahr 2-3, idiopathic PD who had fallen in the year prior to enrolment. Individuals were assessed at baseline and followed up at eight months, including determination of frailty status. RESULTS: 120 patients attended for follow-up. At follow-up, the mean (SD) age was 70.2 years (8.0), MDS-UPDRS total score 91.5 (29.1), and MDS-UPDRS motor score (Part III) 42.7 (14.8). Median disease duration was 9.2 years (IQR 4.6 to 13.1), Geriatric Depression Score 4 (IQR 2 to 6). Using the Fried frailty criteria, 31 (26%) were frail and 70 (58%) pre-frail. In univariable analysis, being female, higher depression score, and MDS-UPDRS score were associated with greater frailty. Using ordinal regression, in the multivariable model, being female (odds ratio [OR] 3.10, 95%CI 1.53 to 6.26, p=.002), higher total MDS-UPDRS score (OR 2.02, 95%CI 1.42 to 2.87, p<.0001) and higher depression (OR 1.47, 95%CI 1.05 to 2.06, p=.03) were associated with higher number of frailty markers. CONCLUSION: There was a high prevalence (84%) of pre-frail and frail individuals in patients participating in this RCT. Future research should determine the optimum tool to assess frailty in this at-risk population, and delineate the association between Parkinson's, frailty, and health outcomes.

Protocol for PD SENSORS: Parkinson's Disease Symptom Evaluation in a Naturalistic Setting producing Outcome measuRes using SPHERE technology. An observational feasibility study of multi-modal multi-sensor technology to measure symptoms and activities of daily living in Parkinson's disease.

INTRODUCTION: The impact of disease-modifying agents on disease progression in Parkinson's disease is largely assessed in clinical trials using clinical rating scales. These scales have drawbacks in terms of their ability to capture the fluctuating nature of symptoms while living in a naturalistic environment. The SPHERE (Sensor Platform for HEalthcare in a Residential Environment) project has designed a multi-sensor platform with multimodal devices designed to allow continuous, relatively inexpensive, unobtrusive sensing of motor, non-motor and activities of daily living metrics in a home or a home-like environment. The aim of this study is to evaluate how the SPHERE technology can measure aspects of Parkinson's disease. METHODS AND ANALYSIS: This is a small-scale feasibility and acceptability study during which 12 pairs of participants (comprising a person with Parkinson's and a healthy control participant) will stay and live freely for 5 days in a home-like environment embedded with SPHERE technology including environmental, appliance monitoring, wrist-worn accelerometry and camera sensors. These data will be collected alongside clinical rating scales, participant diary entries and expert clinician annotations of colour video images. Machine learning will be used to look for a signal to discriminate between Parkinson's disease and control, and between Parkinson's disease symptoms 'on' and 'off' medications. Additional outcome measures including bradykinesia, activity level, sleep parameters and some activities of daily living will be explored. Acceptability of the technology will be evaluated qualitatively using semi-structured interviews. ETHICS AND DISSEMINATION: Ethical approval has been given to commence this study; the results will be disseminated as widely as appropriate.

Clinical Outcome of "Asleep" Deep Brain Stimulation for Parkinson Disease Using Robot-Assisted Delivery and Anatomic Targeting of the Subthalamic Nucleus: A Series of 152 Patients.

BACKGROUND: Recent advances in methods used for deep brain stimulation (DBS) include subthalamic nucleus electrode implantation in the "asleep" patient without the traditional use of microelectrode recordings or intraoperative test stimulation. OBJECTIVE: To examine the clinical outcome of patients who have undergone "asleep" DBS for the treatment of Parkinson disease using robot-assisted electrode delivery. METHODS: This is a retrospective review of clinical outcomes of 152 consecutive patients. Their outcomes at 1 yr postimplantation are reported; these include Unified Parkinson's Disease Rating Scale (UPDRS) assessment, Tinetti Mobility Test, Parkinson's Disease Questionnaire (PDQ)-39 quality of life assessment, Mattis Dementia Rating Scale, Beck Depression Inventory, and Beck Anxiety. We also report on a new parietal trajectory for electrode implantation. RESULTS: A total of 152 patients underwent assessment at 1 yr. UPDRS III improved from 39 to 20.5 (47%, P < .001). The total UPDRS score improved from 67.6 to 36.4 (46%, P < .001). UPDRS II scores improved from 18.9 to 10.5 (44%, P < .001) and UPDRS IV scores improved from 7.1 to 3.6 (49%, P < .001). There was a significant reduction in levodopa equivalent daily dose after surgery (mean: 35%, P < .001). PDQ-39 summary index improved by a mean of 7.1 points. There was no significant difference found in clinical outcomes between the frontal and parietal approaches. CONCLUSION: "Asleep" robot-assisted DBS of the subthalamic nucleus demonstrates comparable outcomes with traditional techniques in the treatment of Parkinson disease.

A Neurologist's Guide to REM Sleep Behavior Disorder.

REM Sleep Behavior Disorder (RBD) is a chronic sleep condition characterized by dream enactment and loss of REM atonia. Individuals often present to clinic with complaints of injury to themselves or their bed-partner due to violent movements during sleep. RBD patients have a high risk of developing one of the neurodegenerative α-synucleinopathy diseases: over 70% will develop parkinsonism or dementia within 12 years of their diagnosis. RBD patients also exhibit accelerated disease progression and a more severe phenotype than α-synucleinopathy sufferers without RBD. The disease's low prevalence and the relatively limited awareness of the condition amongst medical professionals makes the diagnosis and treatment of RBD challenging. Uncertainty in patient management is further exacerbated by a lack of clinical guidelines for RBD patient care. There are no binary prognostic markers for RBD disease course and there are no clinical guidelines for neurodegeneration scaling or tracking in these patients. Both clinicians and patients are therefore forced to deal with uncertain outcomes. In this review, we summarize RBD pathology and differential diagnoses, diagnostic, and treatment guidelines as well as prognostic recommendations with a look to current research in the scientific field. We aim to raise awareness and develop a framework for best practice for RBD patient management.