The effect of a change in antihypertensive treatment on orthostatic hypotension in older adults: A systematic review and meta-analysis.

BACKGROUND: Orthostatic hypotension (OH) is common in older adults with hypertension. Antihypertensive treatment (AHT) prevents cardio- and cerebrovascular events. However, physicians are concerned to cause OH, making them hesitant to initiate or augment AHT in older adults with hypertension. METHODS: We systematically researched electronic databases for trials with older participants (≥65 years) with hypertension and OH assessment after initiating, discontinuing, or augmenting AHT. Study quality was assessed using the ROBINS-I tool. Meta-analyses on OH prevalence and postural blood pressure (BP) drop were performed. RESULTS: Twenty-five studies (26,695 participants) met inclusion criteria, of which fifteen could be included in the meta-analyses. OH prevalence decreased after AHT initiation or augmentation (risk ratio 0.39 (95 % CI = 0.21-0.72; I2 = 47 %; p < 0.01), n = 6 studies), but also after AHT discontinuation (risk ratio 0.39 (95 % CI = 0.28-0.55; I2 = 0 %; p < 0.01), n = 2 studies). Postural BP drop did not change after initiation or augmentation of AHT (mean difference 1.07 (95 % CI = -0.49-2.64; I2 = 92 %; p = 0.18), n = 11 studies). The main reason for ten studies not to be included in the meta-analyses was absence of baseline OH data. Most of these studies reported OH incidences between 0 and 2 %. Studies were heterogeneous in OH assessment methods (postural change, timing of BP measurements, and OH definition). Risk of bias was moderate to serious in twenty studies. CONCLUSION: Results suggest that AHT initiation or augmentation decreases OH prevalence, implying that the risk of inducing OH may be overestimated in current AHT decision-making in older adults. However, the overall low level of evidence and the finding that AHT discontinuation reduces OH prevalence limit firm conclusions at present and highlight an important research gap. Future AHT trials in older adults should measure OH in a standardized protocol, adhering to consensus guidelines to overcome these limitations.

Gaze-contingent processing improves mobility, scene recognition and visual search in simulated head-steered prosthetic vision.

Objective.The enabling technology of visual prosthetics for the blind is making rapid progress. However, there are still uncertainties regarding the functional outcomes, which can depend on many design choices in the development. In visual prostheses with a head-mounted camera, a particularly challenging question is how to deal with the gaze-locked visual percept associated with spatial updating conflicts in the brain. The current study investigates a recently proposed compensation strategy based on gaze-contingent image processing with eye-tracking. Gaze-contingent processing is expected to reinforce natural-like visual scanning and reestablished spatial updating based on eye movements. The beneficial effects remain to be investigated for daily life activities in complex visual environments.Approach.The current study evaluates the benefits of gaze-contingent processing versus gaze-locked and gaze-ignored simulations in the context of mobility, scene recognition and visual search, using a virtual reality simulated prosthetic vision paradigm with sighted subjects.Main results.Compared to gaze-locked vision, gaze-contingent processing was consistently found to improve the speed in all experimental tasks, as well as the subjective quality of vision. Similar or further improvements were found in a control condition that ignores gaze-dependent effects, a simulation that is unattainable in the clinical reality.Significance.Our results suggest that gaze-locked vision and spatial updating conflicts can be debilitating for complex visually-guided activities of daily living such as mobility and orientation. Therefore, for prospective users of head-steered prostheses with an unimpaired oculomotor system, the inclusion of a compensatory eye-tracking system is strongly endorsed.

Towards biologically plausible phosphene simulation for the differentiable optimization of visual cortical prostheses.

Blindness affects millions of people around the world. A promising solution to restoring a form of vision for some individuals are cortical visual prostheses, which bypass part of the impaired visual pathway by converting camera input to electrical stimulation of the visual system. The artificially induced visual percept (a pattern of localized light flashes, or 'phosphenes') has limited resolution, and a great portion of the field's research is devoted to optimizing the efficacy, efficiency, and practical usefulness of the encoding of visual information. A commonly exploited method is non-invasive functional evaluation in sighted subjects or with computational models by using simulated prosthetic vision (SPV) pipelines. An important challenge in this approach is to balance enhanced perceptual realism, biologically plausibility, and real-time performance in the simulation of cortical prosthetic vision. We present a biologically plausible, PyTorch-based phosphene simulator that can run in real-time and uses differentiable operations to allow for gradient-based computational optimization of phosphene encoding models. The simulator integrates a wide range of clinical results with neurophysiological evidence in humans and non-human primates. The pipeline includes a model of the retinotopic organization and cortical magnification of the visual cortex. Moreover, the quantitative effects of stimulation parameters and temporal dynamics on phosphene characteristics are incorporated. Our results demonstrate the simulator's suitability for both computational applications such as end-to-end deep learning-based prosthetic vision optimization as well as behavioral experiments. The modular and open-source software provides a flexible simulation framework for computational, clinical, and behavioral neuroscientists working on visual neuroprosthetics.

The effect of doorway characteristics on freezing of gait in Parkinson's disease.

Background: Freezing of gait is a debilitating symptom in Parkinson's disease, during which a sudden motor block prevents someone from moving forward. Remarkably, doorways can provoke freezing. Most research has focused on the influence of doorway width, and little is known about other doorway characteristics influencing doorway freezing. Objective: Firstly, to provide guidelines on how to design doorways for people with freezing. Secondly, to compare people with doorway freezing to people without doorway freezing, and to explore the underlying mechanisms of doorway freezing. Methods: We designed a web-based, structured survey consisting of two parts. Part I (n = 171 responders), open to people with Parkinson's disease with freezing in general, aimed to compare people with doorway freezing to people without doorway freezing. We explored underlying processes related to doorway freezing with the Gait-Specific Attention Profile (G-SAP), inquiring about conscious movement processes occurring during doorway passing. Part II (n = 60), open for people experiencing weekly doorway freezing episodes, inquired about the influence of specific doorway characteristics on freezing. Results: People with doorway freezing (69% of Part I) had higher freezing severity, longer disease duration, and scored higher on all sub scores of the G-SAP (indicating heightened motor, attentional, and emotional thoughts when passing through doorways) than people without doorway freezing. The main categories provoking doorway freezing were: dimensions of the door and surroundings, clutter around the door, lighting conditions, and automatic doors. Conclusion: We provide recommendations on how to maximally avoid freezing in a practical setting. Furthermore, we suggest that doorways trigger freezing based on visuomotor, attentional, and emotional processes.

The role of wrist-worn technology in the management of Parkinson's disease in daily life: A narrative review.

Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Its slow and heterogeneous progression over time makes timely diagnosis challenging. Wrist-worn digital devices, particularly smartwatches, are currently the most popular tools in the PD research field due to their convenience for long-term daily life monitoring. While wrist-worn sensing devices have garnered significant interest, their value for daily practice is still unclear. In this narrative review, we survey demographic, clinical and technological information from 39 articles across four public databases. Wrist-worn technology mainly monitors motor symptoms and sleep disorders of patients in daily life. We find that accelerometers are the most commonly used sensors to measure the movement of people living with PD. There are few studies on monitoring the disease progression compared to symptom classification. We conclude that wrist-worn sensing technology might be useful to assist in the management of PD through an automatic assessment based on patient-provided daily living information.

Dealing with the heterogeneous presentations of freezing of gait: how reliable are the freezing index and heart rate for freezing detection?

BACKGROUND: Freezing of gait (FOG) is an unpredictable gait arrest that hampers the lives of 40% of people with Parkinson's disease. Because the symptom is heterogeneous in phenotypical presentation (it can present as trembling/shuffling, or akinesia) and manifests during various circumstances (it can be triggered by e.g. turning, passing doors, and dual-tasking), it is particularly difficult to detect with motion sensors. The freezing index (FI) is one of the most frequently used accelerometer-based methods for FOG detection. However, it might not adequately distinguish FOG from voluntary stops, certainly for the akinetic type of FOG. Interestingly, a previous study showed that heart rate signals could distinguish FOG from stopping and turning movements. This study aimed to investigate for which phenotypes and evoking circumstances the FI and heart rate might provide reliable signals for FOG detection. METHODS: Sixteen people with Parkinson's disease and daily freezing completed a gait trajectory designed to provoke FOG including turns, narrow passages, starting, and stopping, with and without a cognitive or motor dual-task. We compared the FI and heart rate of 378 FOG events to baseline levels, and to stopping and normal gait events (i.e. turns and narrow passages without FOG) using mixed-effects models. We specifically evaluated the influence of different types of FOG (trembling vs akinesia) and triggering situations (turning vs narrow passages; no dual-task vs cognitive dual-task vs motor dual-task) on both outcome measures. RESULTS: The FI increased significantly during trembling and akinetic FOG, but increased similarly during stopping and was therefore not significantly different from FOG. In contrast, heart rate change during FOG was for all types and during all triggering situations statistically different from stopping, but not from normal gait events. CONCLUSION: When the power in the locomotion band (0.5-3 Hz) decreases, the FI increases and is unable to specify whether a stop is voluntary or involuntary (i.e. trembling or akinetic FOG). In contrast, the heart rate can reveal whether there is the intention to move, thus distinguishing FOG from stopping. We suggest that the combination of a motion sensor and a heart rate monitor may be promising for future FOG detection.

Capturing postural blood pressure dynamics with near-infrared spectroscopy-measured cerebral oxygenation.

Orthostatic hypotension (OH) is highly prevalent in older adults and associated with dizziness, falls, lower physical and cognitive function, cardiovascular disease, and mortality. OH is currently diagnosed in a clinical setting with single-time point cuff measurements. Continuous blood pressure (BP) devices can measure OH dynamics but cannot be used for daily life monitoring. Near-infrared spectroscopy (NIRS) has potential diagnostic value in measuring cerebral oxygenation continuously over a longer time period, but this needs further validation. This study aimed to compare NIRS-measured (cerebral) oxygenation with continuous BP and transcranial Doppler-measured cerebral blood velocity (CBv) during postural changes. This cross-sectional study included 41 participants between 20 and 88 years old. BP, CBv, and cerebral (long channels) and superficial (short channels) oxygenated hemoglobin (O2Hb) were measured continuously during various postural changes. Pearson correlations between BP, CBv, and O2Hb were calculated over curves and specific characteristics (maximum drop amplitude and recovery). BP and O2Hb only showed good curve-based correlations (0.58-0.75) in the initial 30 s after standing up. Early (30-40 s) and 1-min BP recovery associated significantly with O2Hb, but no consistent associations were found for maximum drop amplitude and late (60-175 s) recovery values. Associations between CBv and O2Hb were poor, but stronger for long-channel than short-channel measurements. BP associated well with NIRS-measured O2Hb in the first 30 s after postural change. Stronger associations for CBv with long-channel O2Hb suggest that long-channel NIRS specifically reflects cerebral blood flow during postural transitions, necessary to better understand the consequences of OH such as intolerance symptoms.

fNIRS is sensitive to leg activity in the primary motor cortex after systemic artifact correction.

BACKGROUND: functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool to study cortical activity during movement and gait that requires further validation. This study aimed to assess (1) whether fNIRS can detect the difficult-to-measure leg area of the primary motor cortex (M1) and distinguish it from the hand area; and (2) whether fNIRS can differentiate between automatic (i.e., not requiring one's attention) and non-automatic movement processes. Special attention was attributed to systemic artifacts (i.e., changes in blood pressure, heart rate, breathing) which were assessed and corrected by short channels, i.e., fNIRS channels which are mainly sensitive to superficial scalp hemodynamics. METHODS: Twenty-three seated, healthy participants tapped four fingers on a keyboard or tapped the right foot on four squares on the floor in a specific order given by a 12-digit sequence (e.g., 434141243212). Two different sequences were executed: a beforehand learned (i.e., automatic) version and a newly learned (i.e., non-automatic) version. A 36-channel fNIRS device including 12 short channels covered multiple motor-related cortical areas including M1. The fNIRS data were analyzed with a general linear model (GLM). Correlation between the expected functional hemodynamic responses (i.e. task regressor) and the short channels (i.e. nuisance regressors), necessitated performing a separate short channel regression instead of integrating them in the GLM. RESULTS: Consistent with the M1 somatotopy, we found significant HbO increases of very large effect size in the lateral M1 channels during finger tapping (Cohen's d = 1.35, p<0.001) and significant HbO increases of moderate effect size in the medial M1 channels during foot tapping (Cohen's d = 0.8, p<0.05). The cortical activity differences between automatic and non-automatic tasks were not significantly different. Importantly, leg movements produced large systemic fluctuations, which were adequately removed by the use of all available short channels. DISCUSSION: Our results indicate that fNIRS is sensitive to leg activity in M1, though the sensitivity is lower than for finger activity and requires rigorous correction for systemic fluctuations. We furthermore highlight that systemic artifacts may result in an unreliable GLM analysis when short channels show signals that are similar to the expected hemodynamic responses.

Comparison of state-of-the-art deep learning architectures for detection of freezing of gait in Parkinson's disease.

Introduction: Freezing of gait (FOG) is one of the most debilitating motor symptoms experienced by patients with Parkinson's disease (PD). FOG detection is possible using acceleration data from wearable sensors, and a convolutional neural network (CNN) is often used to determine the presence of FOG epochs. We compared the performance of a standard CNN for the detection of FOG with two more complex networks, which are well suited for time series data, the MiniRocket and the InceptionTime. Methods: We combined acceleration data of people with PD across four studies. The final data set was split into a training (80%) and hold-out test (20%) set. A fifth study was included as an unseen test set. The data were windowed (2 s) and five-fold cross-validation was applied. The CNN, MiniRocket, and InceptionTime models were evaluated using a receiver operating characteristic (ROC) curve and its area under the curve (AUC). Multiple sensor configurations were evaluated for the best model. The geometric mean was subsequently calculated to select the optimal threshold. The selected model and threshold were evaluated on the hold-out and unseen test set. Results: A total of 70 participants (23.7 h, 9% FOG) were included in this study for training and testing, and in addition, 10 participants provided an unseen test set (2.4 h, 11% FOG). The CNN performed best (AUC = 0.86) in comparison to the InceptionTime (AUC = 0.82) and MiniRocket (AUC = 0.76) models. For the CNN, we found a similar performance for a seven-sensor configuration (lumbar, upper and lower legs and feet; AUC = 0.86), six-sensor configuration (upper and lower legs and feet; AUC = 0.87), and two-sensor configuration (lower legs; AUC = 0.86). The optimal threshold of 0.45 resulted in a sensitivity of 77% and a specificity of 58% for the hold-out set (AUC = 0.72), and a sensitivity of 85% and a specificity of 68% for the unseen test set (AUC = 0.90). Conclusion: We confirmed that deep learning can be used to detect FOG in a large, heterogeneous dataset. The CNN model outperformed more complex networks. This model could be employed in future personalized interventions, with the ultimate goal of using automated FOG detection to trigger real-time cues to alleviate FOG in daily life.

The Gray Area of Freezing of Gait Annotation: A Guideline and Open-Source Practical Tool.

Background: Freezing of gait, a disabling episodic symptom, is difficult to assess as the exact begin- and endpoint of an episode is not easy to specify. This hampers scientific and clinical progress. The current golden standard is video annotation by two independent raters. However, the comparison of the two ratings gives rise to non-overlapping, gray areas. Objective: To provide a guideline for dealing with these gray areas. Methods/Results: We propose a standardized procedure for handling the gray areas based on two parameters, the tolerance and correction parameter. Furthermore, we recommend the use of positive agreement, negative agreement, and prevalence index to report interrater agreement instead of the commonly used intraclass correlation coefficient or Cohen's kappa. This theoretical guideline was implemented in an open-source practical tool, FOGtool (https://github.com/helenacockx/FOGtool). Conclusion: This paper aims to contribute to the standardization of freezing of gait assessment, thereby improving data sharing procedures and replicability of study results.

Cognitive map formation supported by auditory, haptic, and multimodal information in persons with blindness.

For efficient navigation, the brain needs to adequately represent the environment in a cognitive map. In this review, we sought to give an overview of literature about cognitive map formation based on non-visual modalities in persons with blindness (PWBs) and sighted persons. The review is focused on the auditory and haptic modalities, including research that combines multiple modalities and real-world navigation. Furthermore, we addressed implications of route and survey representations. Taking together, PWBs as well as sighted persons can build up cognitive maps based on non-visual modalities, although the accuracy sometime somewhat differs between PWBs and sighted persons. We provide some speculations on how to deploy information from different modalities to support cognitive map formation. Furthermore, PWBs and sighted persons seem to be able to construct route as well as survey representations. PWBs can experience difficulties building up a survey representation, but this is not always the case, and research suggests that they can acquire this ability with sufficient spatial information or training. We discuss possible explanations of these inconsistencies.

Cognitive map formation through tactile map navigation in visually impaired and sighted persons.

The human brain can form cognitive maps of a spatial environment, which can support wayfinding. In this study, we investigated cognitive map formation of an environment presented in the tactile modality, in visually impaired and sighted persons. In addition, we assessed the acquisition of route and survey knowledge. Ten persons with a visual impairment (PVIs) and ten sighted control participants learned a tactile map of a city-like environment. The map included five marked locations associated with different items. Participants subsequently estimated distances between item pairs, performed a direction pointing task, reproduced routes between items and recalled item locations. In addition, we conducted questionnaires to assess general navigational abilities and the use of route or survey strategies. Overall, participants in both groups performed well on the spatial tasks. Our results did not show differences in performance between PVIs and sighted persons, indicating that both groups formed an equally accurate cognitive map. Furthermore, we found that the groups generally used similar navigational strategies, which correlated with performance on some of the tasks, and acquired similar and accurate route and survey knowledge. We therefore suggest that PVIs are able to employ a route as well as survey strategy if they have the opportunity to access route-like as well as map-like information such as on a tactile map.

End-to-end optimization of prosthetic vision.

Neural prosthetics may provide a promising solution to restore visual perception in some forms of blindness. The restored prosthetic percept is rudimentary compared to normal vision and can be optimized with a variety of image preprocessing techniques to maximize relevant information transfer. Extracting the most useful features from a visual scene is a nontrivial task and optimal preprocessing choices strongly depend on the context. Despite rapid advancements in deep learning, research currently faces a difficult challenge in finding a general and automated preprocessing strategy that can be tailored to specific tasks or user requirements. In this paper, we present a novel deep learning approach that explicitly addresses this issue by optimizing the entire process of phosphene generation in an end-to-end fashion. The proposed model is based on a deep auto-encoder architecture and includes a highly adjustable simulation module of prosthetic vision. In computational validation experiments, we show that such an approach is able to automatically find a task-specific stimulation protocol. The results of these proof-of-principle experiments illustrate the potential of end-to-end optimization for prosthetic vision. The presented approach is highly modular and our approach could be extended to automated dynamic optimization of prosthetic vision for everyday tasks, given any specific constraints, accommodating individual requirements of the end-user.

Real-world indoor mobility with simulated prosthetic vision: The benefits and feasibility of contour-based scene simplification at different phosphene resolutions.

Neuroprosthetic implants are a promising technology for restoring some form of vision in people with visual impairments via electrical neurostimulation in the visual pathway. Although an artificially generated prosthetic percept is relatively limited compared with normal vision, it may provide some elementary perception of the surroundings, re-enabling daily living functionality. For mobility in particular, various studies have investigated the benefits of visual neuroprosthetics in a simulated prosthetic vision paradigm with varying outcomes. The previous literature suggests that scene simplification via image processing, and particularly contour extraction, may potentially improve the mobility performance in a virtual environment. In the current simulation study with sighted participants, we explore both the theoretically attainable benefits of strict scene simplification in an indoor environment by controlling the environmental complexity, as well as the practically achieved improvement with a deep learning-based surface boundary detection implementation compared with traditional edge detection. A simulated electrode resolution of 26 × 26 was found to provide sufficient information for mobility in a simple environment. Our results suggest that, for a lower number of implanted electrodes, the removal of background textures and within-surface gradients may be beneficial in theory. However, the deep learning-based implementation for surface boundary detection did not improve mobility performance in the current study. Furthermore, our findings indicate that, for a greater number of electrodes, the removal of within-surface gradients and background textures may deteriorate, rather than improve, mobility. Therefore, finding a balanced amount of scene simplification requires a careful tradeoff between informativity and interpretability that may depend on the number of implanted electrodes.

Determinants of orthostatic cerebral oxygenation assessed using near-infrared spectroscopy.

BACKGROUND: To understand the relationship between blood pressure changes during standing up and clinical outcome, cerebral oxygenation needs to be measured, which may be performed using near-infrared spectroscopy (NIRS). However, the role of potential determinants of NIRS-derived orthostatic cerebral oxygenation, i.e., age, sex, type of postural change (i.e., standing up from sitting versus supine position), blood pressure (BP) and baroreflex sensitivity (BRS) is still unknown and needed to better interpret findings from studies using orthostatic NIRS measurements. METHODS: 34 younger (median age 25 years, inter quartile range (IQR) 22-45) and 31 older adults (median age 77 years, IQR 72-81) underwent BP, BRS and NIRS measurements during standing up from sitting and supine position. Linear regression models were used to assess the potential determinant role of age, sex, type of postural change, BP and BRS in orthostatic cerebral oxygenation drop and recovery. Orthostatic cerebral oxygenation test-retest reliability was assessed using intra class correlations. RESULTS: Younger age, male sex and standing up from supine compared to sitting position were positively associated with cerebral oxygenation drop; older age and standing up from sitting compared to supine position were associated with higher cerebral oxygenation recovery. Test-retest reliability was highest (ICC > 0.83) during standing up from supine position. CONCLUSION: Based on the findings of this study, age, sex and type of postural change are significant determinants of NIRS-derived orthostatic cerebral oxygenation and should be taken into account in the interpretation of NIRS measurements. In the design of new studies, standing up from supine position is preferable (higher reliability) over standing up from sitting position.

Orthostatic Blood Pressure Recovery Measured Using a Sphygmomanometer Is Not Associated with Physical Performance or Number of Falls in Geriatric Outpatients.

BACKGROUND: Orthostatic hypotension (OH) and impaired OH recovery derived from beat-to-beat blood pressure (BP) measurements are associated with detrimental clinical outcome, but the clinical relevance of OH recovery assessed using the widely available sphygmomanometer is still unclear. METHOD: 635 geriatric outpatients underwent comprehensive geriatric assessment, including orthostatic BP measurements using a sphygmomanometer, during supine rest and 1 and 3 min after standing up and assessment of physical performance (i.e., the timed up and go test and the Short Physical Performance Battery) and the number of falls in the past year. The association between BP recovery, defined as BP at 3 min minus BP at 1 min after standing up, with physical performance and falls was assessed using regression analyses, adjusting for age and sex, both in the entire cohort and after stratifying for the presence of OH at 1 min after standing up. RESULTS: BP recovery was not associated with physical performance or number of falls, neither in the entire cohort, nor in subpopulations with or without OH. CONCLUSION: The clinical relevance of BP recovery between 1 and 3 min after standing up could not be demonstrated. The results suggest that sphygmomanometer measurements have an inadequate time resolution to record the clinically relevant dynamics of orthostatic BP recovery.

Validation of Soft Multipin Dry EEG Electrodes.

Current developments towards multipin, dry electrodes in electroencephalography (EEG) are promising for applications in non-laboratory environments. Dry electrodes do not require the application of conductive gel, which mostly confines the use of gel EEG systems to the laboratory environment. The aim of this study is to validate soft, multipin, dry EEG electrodes by comparing their performance to conventional gel EEG electrodes. Fifteen healthy volunteers performed three tasks, with a 32-channel gel EEG system and a 32-channel dry EEG system: the 40 Hz Auditory Steady-State Response (ASSR), the checkerboard paradigm, and an eyes open/closed task. Within-subject analyses were performed to compare the signal quality in the time, frequency, and spatial domains. The results showed strong similarities between the two systems in the time and frequency domains, with strong correlations of the visual (ρ = 0.89) and auditory evoked potential (ρ = 0.81), and moderate to strong correlations for the alpha band during eye closure (ρ = 0.81-0.86) and the 40 Hz-ASSR power (ρ = 0.66-0.72), respectively. However, delta and theta band power was significantly increased, and the signal-to-noise ratio was significantly decreased for the dry EEG system. Topographical distributions were comparable for both systems. Moreover, the application time of the dry EEG system was significantly shorter (8 min). It can be concluded that the soft, multipin dry EEG system can be used in brain activity research with similar accuracy as conventional gel electrodes.