Postural Transitions Research Articles

Activity recognition for elderly care using genetic search

The advent of newer and better technologies has made Human Activity Recognition (HAR) highly essential in our daily lives. HAR is a classification problem where the activity of humans is classified by analyzing the data collected from various sources like sensors, cameras etc. for a period of time. In this work, we have proposed a model for activity recognition which will provide a substructure for the assisted living environment. We used a genetic search based feature selection for the management of the voluminous data generated from various embedded sensors such as accelerometer, gyroscope, etc. We evaluated the proposed model on a sensor-based dataset - Human Activities and Postural Transitions Recognition (HAPT) which is publically available. The proposed model yields an accuracy of 97.04% and is better as compared to the other existing classification algorithms on the basis of several considered evaluation metrics. In this paper, we have also presented a cloud based edge computing architecture for the deployment of the proposed model which will ensure faster and uninterrupted assisted living environment.

Passive Lower Limb Exoskeleton for Kneeling and Postural Transition Assistance With Expanded Support Polygon

Passive Lower Limb Exoskeleton for Kneeling and Postural Transition Assistance With Expanded Support Polygon

The Effect of a Smartphone App with an Accelerometer on the Physical Activity Behavior of Hospitalized Patients: A Randomized Controlled Trial.

Inactive behavior is common in hospitalized patients. This study investigated the effectiveness of using a smartphone app with an accelerometer (Hospital Fit) in addition to usual care physiotherapy on increasing patients' physical activity (PA) behavior. A randomized controlled trial was performed at Maastricht University Medical Centre. Patients receiving physiotherapy while hospitalized at the department of Pulmonology or Internal Medicine were randomized to usual care physiotherapy or using Hospital Fit additionally. Daily time spent walking, standing, and upright (standing/walking) (min) and daily number of postural transitions were measured with an accelerometer between the first and last treatment. Multiple linear regression analysis was performed to determine the association between PA behavior and Hospital Fit use, corrected for functional independence (mILAS). Seventy-eight patients were included with a median (IQR) age of 63 (56-68) years. Although no significant effects were found, a trend was seen in favor of Hospital Fit. Effects increased with length of use. Corrected for functional independence, Hospital Fit use resulted in an average increase of 27.4 min (95% CI: -2.4-57.3) standing/walking on day five and 29.2 min (95% CI: -6.4-64.7) on day six compared to usual care. Hospital Fit appears valuable in increasing PA in functionally independent patients.

Human Posture Transition-Time Detection Based upon Inertial Measurement Unit and Long Short-Term Memory Neural Networks.

As human-robot interaction becomes more prevalent in industrial and clinical settings, detecting changes in human posture has become increasingly crucial. While recognizing human actions has been extensively studied, the transition between different postures or movements has been largely overlooked. This study explores using two deep-learning methods, the linear Feedforward Neural Network (FNN) and Long Short-Term Memory (LSTM), to detect changes in human posture among three different movements: standing, walking, and sitting. To explore the possibility of rapid posture-change detection upon human intention, the authors introduced transition stages as distinct features for the identification. During the experiment, the subject wore an inertial measurement unit (IMU) on their right leg to measure joint parameters. The measurement data were used to train the two machine learning networks, and their performances were tested. This study also examined the effect of the sampling rates on the LSTM network. The results indicate that both methods achieved high detection accuracies. Still, the LSTM model outperformed the FNN in terms of speed and accuracy, achieving 91% and 95% accuracy for data sampled at 25 Hz and 100 Hz, respectively. Additionally, the network trained for one test subject was able to detect posture changes in other subjects, demonstrating the feasibility of personalized or generalized deep learning models for detecting human intentions. The accuracies for posture transition time and identification at a sampling rate of 100 Hz were 0.17 s and 94.44%, respectively. In summary, this study achieved some good outcomes and laid a crucial foundation for the engineering application of digital twins, exoskeletons, and human intention control.

Postexercise cardiovascular hemodynamics assessment before and after a 30-minute standing still recovery.

Although postexercise syncope usually occurs shortly after physical exercise conclusion, athletes commonly reveal symptoms of postexercise hypotension several tens of minutes after exercise completion. Currently, no studies have investigated central hemodynamic regulation during posture changes occurring several tens of minutes after exercise compared to immediately after cessation. This study examined changes in mean arterial pressure (MAP), heart rate (HR), systemic vascular conductance (SVC), cardiac output, and stroke volume during two sets of tilt tests performed before vs. after a 30-minute standing still recovery, respectively. Tilt tests were performed after a short-lasting supramaximal test (WNG) and long-lasting maximal incremental test (INC) in 12 young endurance-trained individuals. The key findings were that, regardless of the exercise type, the 30-minute recovery augmented (P<0.01) the increase in HR and the drop in SVC during the transition from supine to upright, although the MAP drop was similar (P=0.99) after vs. before recovery. INC led to greater increases (P<0.01) in HR and drops (P<0.01) in SVC compared to WNG during postural transitions both before and after the recovery. These findings suggest that, in a population that tolerates postexercise hypotension, MAP neural control is more challenged after a 30-minute standing still recovery than before, as evidenced by an augmented vasodilation capacity along with an increased HR buffering response during posture changes. Moreover, our data suggest that effective MAP control is resulting from an equally effective HR buffering response on MAP. Therefore, exercises that induce greater systemic vasodilation lead to greater HR buffering responses.

Comparative Analysis of the Clustering Quality in Self-Organizing Maps for Human Posture Classification.

The objective of this article is to develop a methodology for selecting the appropriate number of clusters to group and identify human postures using neural networks with unsupervised self-organizing maps. Although unsupervised clustering algorithms have proven effective in recognizing human postures, many works are limited to testing which data are correctly or incorrectly recognized. They often neglect the task of selecting the appropriate number of groups (where the number of clusters corresponds to the number of output neurons, i.e., the number of postures) using clustering quality assessments. The use of quality scores to determine the number of clusters frees the expert to make subjective decisions about the number of postures, enabling the use of unsupervised learning. Due to high dimensionality and data variability, expert decisions (referred to as data labeling) can be difficult and time-consuming. In our case, there is no manual labeling step. We introduce a new clustering quality score: the discriminant score (DS). We describe the process of selecting the most suitable number of postures using human activity records captured by RGB-D cameras. Comparative studies on the usefulness of popular clustering quality scores-such as the silhouette coefficient, Dunn index, Calinski-Harabasz index, Davies-Bouldin index, and DS-for posture classification tasks are presented, along with graphical illustrations of the results produced by DS. The findings show that DS offers good quality in posture recognition, effectively following postural transitions and similarities.

Impact of ischemic heart disease and cardiac rehabilitation on cerebrovascular compliance.

We aimed to determine the influence of ischemic heart disease (IHD) and cardiac rehabilitation (CR) on cerebrovascular compliance index (Ci). Eleven (one female) patients with IHD (mean[SD]: 61[11] yr, 29[4] kg/m2) underwent 6 mo of CR, which consisted of ≥3 sessions/wk of aerobic and resistance training (20-60 min each). Ten (three female) similarly aged controls (CON) were tested at baseline as a comparator group. Middle cerebral artery velocity (MCAv) and mean arterial pressure were monitored continuously using transcranial Doppler ultrasound and finger photoplethysmography, respectively, during a rapid sit-to-stand maneuver. A Windkessel model was used to estimate cerebrovascular Ci every five cardiac cycles for a duration of 30 s. Cerebrovascular resistance was calculated as the quotient of MAP and MCAv. Two-way ANOVAs were used to determine whether cerebrovascular variables differ during postural transitions between groups and after CR. Baseline MCAv was higher in CON versus IHD (P = 0.014) and a time × group interaction was observed (P = 0.045) where MCAv decreased more in CON after standing. Compared with the precondition, CR had no effect on MCAv (condition P = 0.950) but a main effect of time indicated that MCAv decreased from the seated position in both conditions (time P = 0.013). Baseline cerebrovascular Ci was greater in IHD versus CON (P = 0.049) and the peak cerebrovascular Ci during the transition to standing was significantly higher in IHD compared with CON (interaction P = 0.047). CR did not affect cerebrovascular compliance (P = 0.452) and no time-by-condition interaction upon standing was present (P = 0.174). Baseline cerebrovascular Ci is higher in IHD at baseline compared with CON, but 6 mo of CR did not modify the transient increase in cerebrovascular Ci during sit-to-stand maneuvers.NEW & NOTEWORTHY Post-cardiac event cognitive impairment is common and exercise-based rehabilitation may be an effective intervention to mitigate cognitive decline. Microvascular damage due to high blood pressure pulsatility entering the brain is the putative mechanism of vascular dementia. Whether patients with ischemic heart disease exhibit lower cerebrovascular compliance, and if cardiac rehabilitation can improve cerebrovascular compliance is unknown. We observed that patients with ischemic heart disease have paradoxically higher cerebrovascular compliance, which is not affected by cardiac rehabilitation.

Evolution of posture in amniotes-Diving into the trabecular architecture of the femoral head.

Extant amniotes show remarkable postural diversity. Broadly speaking, limbs with erect (strongly adducted, more vertically oriented) posture are found in mammals that are particularly heavy (graviportal) or show good running skills (cursorial), while crouched (highly flexed) limbs are found in taxa with more generalized locomotion. In Reptilia, crocodylians have a "semi-erect" (somewhat adducted) posture, birds have more crouched limbs and lepidosaurs have sprawling (well-abducted) limbs. Both synapsids and reptiles underwent a postural transition from sprawling to more erect limbs during the Mesozoic Era. In Reptilia, this postural change is prominent among archosauriforms in the Triassic Period. However, limb posture in many key Triassic taxa remains poorly known. In Synapsida, the chronology of this transition is less clear, and competing hypotheses exist. On land, the limb bones are subject to various stresses related to body support that partly shape their external and internal morphology. Indeed, bone trabeculae (lattice-like bony struts that form the spongy bone tissue) tend to orient themselves along lines of force. Here, we study the link between femoral posture and the femoral trabecular architecture using phylogenetic generalized least squares. We show that microanatomical parameters measured on bone cubes extracted from the femoral head of a sample of amniote femora depend strongly on body mass, but not on femoral posture or lifestyle. We reconstruct ancestral states of femoral posture and various microanatomical parameters to study the "sprawling-to-erect" transition in reptiles and synapsids, and obtain conflicting results. We tentatively infer femoral posture in several hypothetical ancestors using phylogenetic flexible discriminant analysis from maximum likelihood estimates of the microanatomical parameters. In general, the trabecular network of the femoral head is not a good indicator of femoral posture. However, ancestral state reconstruction methods hold great promise for advancing our understanding of the evolution of posture in amniotes.

Defining and reporting activity patterns: a modified Delphi study

BackgroundDespite significant interest in assessing activity patterns in different populations, there has been no consensus concerning the definition and operationalisation of this term. This has limited the comparability, interpretability, and synthesis of study findings to date. The aim of this study was to establish a consensus regarding the way in which activity patterns and activity pattern components are defined and reported.MethodsThe activity patterns literature was searched to identify experts to be invited to participate and to develop a proposed definition of activity patterns and activity pattern components. A three-round modified Delphi survey was conducted online (November 2021 to May 2022). In Round 1, participants were asked to rate their agreement with a proposed activity patterns definition, which also included six activity pattern components (e.g., activity intensity, activity bout, transitions), six examples of activity patterns (e.g., frequency of postural transitions in discrete time periods) and eight items for reporting activity patterns in future research (n = 21 items). Open-ended questions enabled participants to provide further comments and suggestions for additional items. Consensus was defined a priori as ≥ 80% participants rating their agreement with an item. In Round 2, participants were asked to rate their agreement with 25 items (13 original items, eight amended, and four new). In Round 3, participants rated their agreement with 10 items (five original items, four amended, and one new).ResultsTwenty experts in activity patterns research participated in Round 1, with response rates of 80% and 60% in Rounds 2 and 3, respectively. The proposed activity pattern definition, all activity pattern components definitions, four of the six activity pattern examples, and 10 items in the activity patterns reporting framework achieved consensus. The removal of one activity component item between Rounds 1 and 2 achieved consensus.ConclusionThis modified Delphi study achieved consensus for defining and reporting activity patterns for the first time. This consensus definition enables standardisation of activity patterns terminology, which is important given the significant interest in quantifying how individuals accumulate their physical activity and sedentary behaviour across the lifespan to inform the development of future public health guidelines and interventions efforts.

Self-organizing neural network for reproducing human postural mode alternation through deep reinforcement learning

A self-organized phenomenon in postural coordination is essential for understanding the auto-switching mechanism of in-phase and anti-phase postural coordination modes during standing and related supra-postural activities. Previously, a model-based approach was proposed to reproduce such self-organized phenomenon. However, if we set this problem including the process of how we establish the internal predictive model in our central nervous system, the learning process is critical to be considered for establishing a neural network for managing adaptive postural control. Particularly when body characteristics may change due to growth or aging or are initially unknown for infants, a learning capability can improve the hyper-adaptivity of human motor control for maintaining postural stability and saving energy in daily living. This study attempted to generate a self-organizing neural network that can adaptively coordinate the postural mode without assuming a prior body model regarding body dynamics and kinematics. Postural coordination modes are reproduced in head-target tracking tasks through a deep reinforcement learning algorithm. The transitions between the postural coordination types, i.e. in-phase and anti-phase coordination modes, could be reproduced by changing the task condition of the head tracking target, by changing the frequencies of the moving target. These modes are considered emergent phenomena existing in human head tracking tasks. Various evaluation indices, such as correlation, and relative phase of hip and ankle joint, are analyzed to verify the self-organizing neural network performance to produce the postural coordination transition between the in-phase and anti-phase modes. In addition, after learning, the neural network can also adapt to continuous task condition changes and even to unlearned body mass conditions keeping consistent in-phase and anti-phase mode alternation.

Sensor-Based Assessment of Variability in Daily Physical Activity and Frailty

Introduction: Frailty is a common geriatric syndrome associated with decline in physiological reserve. While several digital biomarkers of daily physical activity (DPA) have been used in frailty assessment, the association between DPA variability and frailty is still not clear. The goal of this study was to determine the association between frailty and DPA variability. Methods: This is an observational cross-sectional study conducted between September 2012 and November 2013. Older adults (≥65 years), without any severe mobility disorder, and the ability to walk 10 m (with or without an assistive device) were eligible for the study. DPA including sitting, standing, walking, lying, and postural transition were recorded for 48 h continuously. DPA variability was analyzed from two perspectives: (i) DPA duration variability in terms of coefficient of variation (CoV) of sitting, standing, walking, and lying down durations; and (ii) DPA performance variability in terms of CoV of sit-to-stand (SiSt) and stand-to-sit (StSi) durations and stride time (i.e., slope of power spectral density – PSD). Results: Data was analyzed from 126 participants (44 non-frail, 60 pre-frail, and 22 frail). For DPA duration variability, CoV of lying and walking duration was significantly larger among non-frail compared to pre-frail and frail groups (p < 0.03, d = 0.89 ± 0.40). For DPA performance variability, StSi CoV and PSD slope were significantly smaller for non-frail compared to pre-frail and frail groups (p < 0.05, d = 0.78 ± 0.19). Conclusion: Lower DPA duration variability in pre-frail and frail groups may be attributed to the set daily routines frail older adults tend to follow, compared to variable physical activity routines of non-frail older adults. Higher DPA performance variability in the frail group may be attributed to reduced physiological capabilities toward walking for longer durations and the reduced muscle strength in the lower extremities, leading to incosistency in performing postural transitions.

Remote multimodal monitoring of motor neuron disease progression using wearable sensors and digital assessments (S14.010)

<h3>Objective:</h3> To develop and assess the feasibility of a robust multi-modal platform to remotely monitor motor neuron disease (MND) symptoms and disease progression using wearable sensors and digital assessments of speech, handwriting, and pattern-tracing skills. <h3>Background:</h3> Frequent remote assessments of different disease symptoms and progression are critical in improving care for patients with neurological disorders and clinical trial readiness. There is a need for a multi-modal technological solution to objectively measure and monitor disease progression in MND. <h3>Design/Methods:</h3> Participants with MND were enrolled for up to 12 months of remote monitoring. They wore PAMSys™ pendant sensors for the duration of study to measure physical activity, walking parameters, postural transition, and falls during activities of daily living. Digital speech and handwriting and pattern tracing skill assessments were performed using the BioDigit Home™ (BioSensics LLC) tablet on biweekly basis. <h3>Results:</h3> To date, nine participants have been enrolled (4 female), with a median age of 69 years (range 44–2 years). High compliance for the pendant-sensor-based physical activity monitoring was observed and provided a reliable tool to assess fall risk in patients with MND (with some subjects having up to 1.5 confirmed falls per week and one reported near fall per week). Furthermore, on average, subjects completed 91.9% (range 53.8%–100%) of assigned speech task. 88% of the participants were able to perform handwriting and pattern-tracing tasks. <h3>Conclusions:</h3> Our preliminary results demonstrate the feasibility of the multi-modal telemonitoring solution to remotely monitor mobility and disease symptoms in MND. The longitudinal monitoring may address the problem of subjective biases, measure functional changes over time, and compensate for the impact of biological variability in intermittent single visits. Patient recruitment and data collection is ongoing, and the most updated results will be presented during the meeting. <b>Disclosure:</b> The institution of Andrew Geronimo has received research support from BioSensics, LLC. Mr. Casado has received personal compensation for serving as an employee of BioSensics LLC. Dr. Mishra has received personal compensation for serving as an employee of Biosensics. Mr. Lim has nothing to disclose. Dr. Vaziri has received personal compensation for serving as an employee of Biosensics. Dr. Simmons has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Cytokinetics. The institution of Dr. Simmons has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Amylyx. Dr. Simmons has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Sanofi. Dr. Simmons has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Alexion. Dr. Simmons has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Biogen. Dr. Simmons has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Alector. Dr. Simmons has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Corcept. The institution of Dr. Simmons has received personal compensation in the range of $100,000-$499,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Wiley. The institution of Dr. Simmons has received research support from MGH. The institution of Dr. Simmons has received research support from MT Pharma. The institution of Dr. Simmons has received research support from University of Kansas. The institution of Dr. Simmons has received research support from ALS Association.

Longitudinal study of Progressive Supranuclear Palsy (PSP) using remote at-home multi-modal digital assessments and wearable devices (S51.002)

<h3>Objective:</h3> To measure Progressive Supranuclear Palsy (PSP) progression remotely in participants’ homes using wearable sensors, digital speech and cognitive assessments. <h3>Background:</h3> There are limited studies using technology to objectively measure disease progression in PSP and no studies using wearable technology in participants’ homes. We hypothesized that remote, objective, quantitative measures of disease progression will facilitate clinical trials and help spur development of new therapies for PSP. <h3>Design/Methods:</h3> Patients with clinically probable PSP by MDS 2017 criteria able to ambulate ≥10 feet unassisted were recruited at Massachusetts General Hospital and Johns Hopkins from November 2021 through September, 2022 and followed virtually monthly for 1 year. Motor assessments performed monthly wearing LEGSys™ and BalanSense™ (BioSensics LLC, Newton, MA USA) devices included: balance assessments, 5x sit-to-stand, 3-meter timed up and go, and 2-minute walk tests. Participants wore PAMSys™ (BioSensics LLC) pendant sensors for 1 year to measure physical activity, walking parameters, postural transitions, and falls during daily activities. Digital cognitive and speech assessments performed using the BioDigit Home™ (BioSensics LLC) tablet every 3 months included: Color Trails, Conflicting Instructions, Go/No-Go, Forward and Backward Digit Span. The PSP Rating Scale (PSPRS), MoCA, PSP-QoL and CBFS were collected virtually every 3 months or in-person. <h3>Results:</h3> As of October 2022, 11 PSP participants were enrolled. By April 2023, 7 participants will have completed 12 months of follow-up. One participant was unable to complete virtual assessments due to lack of caregiver support and 3 participants could not perform walking tasks after 6 months. Walking parameters, postural duration and transition times correlated strongly with disease progression as measured using the PSPRS and PSP-QoL. Instrumented gait measures correlated with activity levels. <h3>Conclusions:</h3> Our study demonstrates the feasibility of remote longitudinal measurement of PSP progression in participants’ homes using wearable devices and digital assessments. The study identifies possible digital biomarkers of PSP progression. <b>Disclosure:</b> Miss Sharma has nothing to disclose. Ms. Hall has received research support from National Institutes of Health. Miss Cole has nothing to disclose. Mr. Casado has received personal compensation for serving as an employee of BioSensics LLC. Dr. Mishra has received personal compensation for serving as an employee of Biosensics. Dr. Vaziri has received personal compensation for serving as an employee of Biosensics. Dr. Pantelyat has received personal compensation for serving as an employee of MedRhythms, Inc.. Dr. Pantelyat has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for MedRhythms, Inc.. Dr. Pantelyat has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Kelly &amp; Ignoffo Law Group. The institution of Dr. Pantelyat has received research support from NIH/NIA. Dr. Wills has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Accordant, a CVS/Caremark company. Dr. Wills has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Sanofi/Genzyme. The institution of Dr. Wills has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Ono Pharmaceuticals. The institution of Dr. Wills has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Amylyx. Dr. Wills has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Parkinson’s Foundation. The institution of Dr. Wills has received research support from Parkinson’s Foundation. The institution of Dr. Wills has received research support from Biogen. The institution of Dr. Wills has received research support from Roche/Genentech. The institution of Dr. Wills has received research support from BioSensics.

Wearable Sensors for Quantitative Motor Assessments in Multiple System Atrophy (P8-9.002)

<h3>Objective:</h3> To determine the utility of quantitative wearable sensors in Multiple system atrophy (MSA). <h3>Background:</h3> Symptoms of MSA include parkinsonism, ataxia, and/or failure of the autonomic nervous system. Wearable sensors have potential to characterize motor impairment in an outpatient setting and to serve as clinical trial outcomes in MSA. <h3>Design/Methods:</h3> Participants enrolled in biomarkers of progression in MSA (bioMUSE) had early MSA (&lt;3 years of motor symptoms) by clinical assessment. All completed neurologic exam, neuroimaging and biofluid assessments. The Unified MSA Rating Scale motor exam (UMSARS II), Parkinson Plus Scale (PPSm), and Tandem Walk (TW), were completed every 3 months. PAMSys actigraphy sensors were worn continuously for up to 12-months to assess gait (step count, bouts of walking, steps per bout, cadence, cadence variability), postures (minutes of sitting, lying, standing, walking, sedentary [sitting + lying]) and postural transitions (sit-to-stand) by averaging data over 14-days. Pearson correlation coefficients between clinical and sensor variables were estimated at each time point and two-sided p-values were calculated. <h3>Results:</h3> 12 participants (6 Female, mean age 64.2) with motor symptoms of 2.X years were followed for ≥ 6 months (n=9), and 12 months (n=5). Significant (<i>P</i>&lt;0.05) correlations were observed between step count, bouts of walking, minutes walking and sit to stand transitions for UMSARS II, PPSm and TW. Significant correlations were most frequently observed at BL and months 3, 6 and 9. The strongest correlations (r&gt;0.8) were observed at month 6 and 9. The PPSm had more frequent and stronger correlation with sensor parameters than UMSARS II. <h3>Conclusions:</h3> In early MSA, continuous actigraphy is feasible and demonstrates significant correlation with motor exam. The PPSm appeared to have stronger correlation with sensor variables than UMSARS II. Continuous motor assessments via wearable sensors may be a suitable endpoint for clinical trials in MSA. <b>Disclosure:</b> Dr. Claassen has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Teva Neuroscience. Dr. Claassen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Spark . The institution of Dr. Claassen has received personal compensation in the range of $50,000-$99,999 for serving as a Consultant for Alterity. Dr. Claassen has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Teva Neuroscience. Dr. Claassen has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for HD Insights. The institution of Dr. Claassen has received research support from NIH. The institution of Dr. Claassen has received research support from CHDI. The institution of Dr. Claassen has received research support from HDSA. The institution of Dr. Claassen has received research support from Department of Defense. The institution of Dr. Claassen has received research support from Griffin Family Foundation. The institution of Dr. Claassen has received research support from Neurocrine. The institution of Dr. Claassen has received research support from Vaccinex. The institution of Dr. Claassen has received research support from AbbVie. The institution of Dr. Claassen has received research support from CHDI. The institution of Dr. Claassen has received research support from Genentech/ Roche. The institution of Dr. Claassen has received research support from Prilenia. The institution of Dr. Claassen has received research support from Neurocrine/ HSG. Miss Iregui has nothing to disclose. Ms. Wynn has nothing to disclose. Charles Davis has nothing to disclose. Cynthia Wong has received personal compensation for serving as an employee of Alterity Therapeutics. Dr. Stamler has received personal compensation for serving as an employee of Alterity Therapeutics.

Center of Pressure Deviation during Posture Transition in Athletes with Chronic Ankle Instability.

Center of pressure (COP) tracking during posture transition is an ideal scale for determining the recurrence of an ankle injury, thereby preventing chronic ankle instability (CAI). However, the same is difficult to determine because the reduced ability of certain patients (who experienced sprain) to control posture at the ankle joint is masked by the chain of hip and ankle joint motion. Thus, we observed the effects of knee joint immobilization/non-immobilization on postural control strategies during the posture transition task and attempted to evaluate the detailed pathophysiology of CAI. Ten athletes with unilateral CAI were selected. To examine differences in COP trajectories in the CAI side and non-CAI legs, patients stood on both legs for 10 s and one leg for 20 s with/without knee braces. COP acceleration during the transition was significantly higher in the CAI group with a knee brace. The COP transition from the double- to single-leg stance phase was significantly longer in the CAI foot. In the CAI group, the fixation of the knee joint increased COP acceleration during postural deviation. This suggests that there is likely an ankle joint dysfunction in the CAI group that is masked by the hip strategy.

Cardiac autonomic modulation in response to postural transition during a virtual reality task in individuals with spinal cord injury: A cross-sectional study.

The postural transition from sitting to standing is a moment of dysautonomic occurrence in individuals with Spinal Cord Injury (SCI). Different tools can be used to minimize this event, such as virtual reality. Thus, we aimed to analyze cardiac autonomic modulation in individuals with SCI during postural transition from the sitting to orthostatism position using a cognitive virtual reality (VR) task. Individuals with and without SCI were positioned on the Easy Stand® device, sitting at rest, at 0° considering the angle between the seat and the floor, elevation at 45°, and orthostatism at 90°, for 5 minutes in each position. Heart rate variability (HRV) measures of sympathovagal balance were collected (heart rate receiver: Polar V800). The groups were subdivided into two groups, one that performed VR as an intervention during the postural angle changes and another group that did not perform VR. We evaluated 76 individuals, 40 with a medical diagnosis of SCI and 36 who composed the able-bodied control group without SCI, matched by age and sex. The HRV results showed that the SCI group who performed the task in VR demonstrated no significant difference in parasympathetic activation and global variability between the sitting versus 90° positions. There was better sympathovagal balance in SCI and able-bodied control groups who performed the VR task between the sitting versus 90° positions. The use of a VR task seems to contribute to better sympathovagal balance, with the potential to reduce dysautonomia during postural changes.

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.

Gait Apraxia and Hakim's Disease: A Historical Review.

In 1965, Prof. Salomón Hakim described, for the first time, a condition characterized by normal pressure hydrocephalus and gait alterations. During the following decades, definitions such as "Frontal Gait", "Bruns' Ataxia" and "Gait Apraxia" have been frequently used in pertinent literature in the attempt to best define this peculiar motor disturbance. More recently, gait analysis has further shed light on the typical spatiotemporal gait alterations that characterize this neurological condition, but a clear and shared definition of this motor condition is still lacking. In this historical review, we described the origins of the terms "Gait Apraxia", "Frontal Gait" and "Bruns' Ataxia", starting with the first works of Carl Maria Finkelburg, Fritsch and Hitzig and Steinthal during the second half of the 19th century and ending with Hakim's studies and his formal definition of idiopathic normal pressure hydrocephalus (iNPH). In the second part of the review, we analyze how and why these definitions of gait have been associated with Hakim's disease in the literature from 1965 to the present day. The definition of "Gait and Postural Transition Apraxia" is then proposed, but fundamental questions about the nature and mechanisms underlying this condition remain unanswered.

Quantifying States and Transitions of Emerging Postural Control for Children Not Yet Able to Sit Independently

Objective, quantitative postural data is limited for individuals who are non-ambulatory, especially for those who have not yet developed trunk control for sitting. There are no gold standard measurements to monitor the emergence of upright trunk control. Quantification of intermediate levels of postural control is critically needed to improve research and intervention for these individuals. Accelerometers and video were used to record postural alignment and stability for eight children with severe cerebral palsy aged 2 to 13 years, under two conditions, seated on a bench with only pelvic support and with additional thoracic support. This study developed an algorithm to classify vertical alignment and states of upright control; Stable, Wobble, Collapse, Rise and Fall from accelerometer data. Next, a Markov chain model was created to calculate a normative score for postural state and transition for each participant with each level of support. This tool allowed quantification of behaviors previously not captured in adult-based postural sway measures. Histogram and video recordings were used to confirm the output of the algorithm. Together, this tool revealed that providing external support allowed all participants: (1) to increase their time spent in the Stable state, and (2) to reduce the frequency of transitions between states. Furthermore, all participants except one showed improved state and transition scores when given external support.

Movement Behavior and Health Outcomes among Sedentary Adults: A Cross-Sectional Study.

Sedentary behavior, which is highly prevalent among office workers, is associated with multiple health disorders, including those of the musculoskeletal and cardiometabolic systems. Although prior studies looked at postures or physical activity during work or leisure time, few analyzed both posture and movement throughout the entire day. This cross-sectional pilot study examined the movement behavior of sedentary office workers during both work and leisure time to explore its association with musculoskeletal discomfort (MSD) and cardiometabolic health indicators. Twenty-six participants completed a survey and wore a thigh-based inertial measuring unit (IMU) to quantify the time spent in different postures, the number of transitions between postures, and the step count during work and leisure time. A heart rate monitor and ambulatory blood pressure cuff were worn to quantify cardiometabolic measures. The associations between movement behavior, MSD, and cardiometabolic health indicators were evaluated. The number of transitions differed significantly between those with and without MSD. Correlations were found between MSD, time spent sitting, and posture transitions. Posture transitions had negative correlations with body mass index and heart rate. Although no single behavior was highly correlated with health outcomes, these correlations suggest that a combination of increasing standing time, walking time, and the number of transitions between postures during both work and leisure time was associated with positive musculoskeletal and cardiometabolic health indicators among sedentary office workers and should be considered in future research.