Accuracy of gait and posture classification using movement sensors in individuals with mobility impairment after stroke

Background: Stroke leads to motor impairment which reduces physical activity, negatively affects social participation, and increases the risk of secondary cardiovascular events. Continuous monitoring of physical activity with motion sensors is promising to allow the prescription of tailored treatments in a timely manner. Accurate classification of gait activities and body posture is necessary to extract actionable information for outcome measures from unstructured motion data. We here develop and validate a solution for various sensor configurations specifically for a stroke population. Methods: Video and movement sensor data (locations: wrists, ankles, and chest) were collected from fourteen stroke survivors with motor impairment who performed real-life activities in their home environment. Video data were labeled for five classes of gait and body postures and three classes of transitions that served as ground truth. We trained support vector machine (SVM), logistic regression (LR), and k-nearest neighbor (kNN) models to identify gait bouts only or gait and posture. Model performance was assessed by the nested leave-one-subject-out protocol and compared across five different sensor placement configurations. Results: Our method achieved very good performance when predicting real-life gait versus non-gait (Gait classification) with an accuracy between 85% and 93% across sensor configurations, using SVM and LR modeling. On the much more challenging task of discriminating between the body postures lying, sitting, and standing as well as walking, and stair ascent/descent (Gait and postures classification), our method achieves accuracies between 80% and 86% with at least one ankle and wrist sensor attached unilaterally. The Gait and postures classification performance between SVM and LR was equivalent but superior to kNN. Conclusion: This work presents a comparison of performance when classifying Gait and body postures in post-stroke individuals with different sensor configurations, which provide options for subsequent outcome evaluation. We achieved accurate classification of gait and postures performed in a real-life setting by individuals with a wide range of motor impairments due to stroke. This validated classifier will hopefully prove a useful resource to researchers and clinicians in the increasingly important field of digital health in the form of remote movement monitoring using motion sensors

Economic Impact of Poststroke Delirium and Associated Risk Factors: Findings From a Prospective Cohort Study

BACKGROUND AND PURPOSE Delirium is a common severe complication of stroke. We aimed to determine the cost-of-illness and risk factors of poststroke delirium (PSD). METHODS This prospective single-center study included n=567 patients with acute stroke from a hospital-wide delirium cohort study and the Swiss Stroke Registry in 2014. Delirium was determined by Delirium Observation Screening Scale or Intensive Care Delirium Screening Checklist 3 times daily during the first 3 days of admission. Costs reflected the case-mix index and diagnosis-related groups from 2014 and were divided into nursing, physician, and total costs. Factors associated with PSD were assessed with multiple regression analysis. Partial correlations and quantile regression were performed to assess costs and other factors associated with PSD. RESULTS The incidence of PSD was 39.0% (221/567). Patients with delirium were older than non-PSD (median 76 versus 70 years; P<0.001), 52% male (115/221) versus 62% non-PSD (214/346) and hospitalized longer (mean 11.5 versus 9.3 days; P<0.001). Dementia was the most relevant predisposing factor for PSD (odds ratio, 16.02 [2.83-90.69], P=0.002). Moderate to severe stroke (National Institutes of Health Stroke Scale score 16-20) was the most relevant precipitating factor (odds ratio, 36.10 [8.15-159.79], P<0.001). PSD was a strong predictor for 3-month mortality (odds ratio, 15.11 [3.33-68.53], P<0.001). Nursing and total costs were nearly twice as high in PSD (P<0.001). There was a positive correlation between total costs and admission National Institutes of Health Stroke Scale (correlation coefficient, 0.491; P<0.001) and length of stay (correlation coefficient, 0.787; P<0.001) in all patients. Quantile regression revealed rising nursing and total costs associated with PSD, higher National Institutes of Health Stroke Scale, and longer hospital stay (all P<0.05). CONCLUSIONS PSD was associated with greater stroke severity, prolonged hospitalization, and increased nursing and total costs. In patients with severe stroke, dementia, or seizures, PSD is anticipated, and additional costs are associated with hospitalization

Consensus-Based Core Set of Outcome Measures for Clinical Motor Rehabilitation After Stroke—A Delphi Study

Introduction: Outcome measures are key to tailor rehabilitation goals to the stroke patient’s individual needs and to monitor poststroke recovery. The large number of available outcome measures leads to high variability in clinical use. Currently, an internationally agreed core set of motor outcome measures for clinical application is lacking. Therefore, the goal was to develop such a set to serve as a quality standard in clinical motor rehabilitation poststroke. Methods: Outcome measures for the upper and lower extremities, and activities of daily living (ADL)/stroke-specific outcomes were identified and presented to stroke rehabilitation experts in an electronic Delphi study. In round 1, clinical feasibility and relevance of the outcome measures were rated on a 7-point Likert scale. In round 2, those rated at least as “relevant” and “feasible” were ranked within the body functions, activities, and participation domains of the International Classification of Functioning, Disability, and Health (ICF). Furthermore, measurement time points poststroke were indicated. In round 3, answers were reviewed in reference to overall results to reach final consensus.This work was financially supported by the P & K Pühringer Foundation

Substance P signalling in primary motor cortex facilitates motor learning in rats.

Among the genes that are up-regulated in response to a reaching training in rats, Tachykinin 1 (Tac1)-a gene that encodes the neuropeptide Substance P (Sub P)-shows an especially strong expression. Using Real-Time RT-PCR, a detailed time-course of Tac1 expression could be defined: a significant peak occurs 7 hours after training ended at the first and second training session, whereas no up-regulation could be detected at a later time-point (sixth training session). To assess the physiological role of Sub P during movement acquisition, microinjections into the primary motor cortex (M1) contralateral to the trained paw were performed. When Sub P was injected before the first three sessions of a reaching training, effectiveness of motor learning became significantly increased. Injections at a time-point when rats already knew the task (i.e. training session ten and eleven) had no effect on reaching performance. Sub P injections did not influence the improvement of performance within a single training session, but retention of performance between sessions became strengthened at a very early stage (i.e. between baseline-training and first training session). Thus, Sub P facilitates motor learning in the very early phase of skill acquisition by supporting memory consolidation. In line with these findings, learning related expression of the precursor Tac1 occurs at early but not at later time-points during reaching training

results_PLCago_SCH23390

Behavior: PLCagonist+D1anta

PLC overtrain_data

Behavior: PLCinh. after learnin

Augmented Reality-Based Rehabilitation of Gait Impairments: Case Report

BACKGROUND Gait and balance impairments are common in neurological diseases, including stroke, and negatively affect patients' quality of life. Improving balance and gait are among the main goals of rehabilitation. Rehabilitation is mainly performed in clinics, which lack context specificity; therefore, training in the patient's home environment is preferable. In the last decade, developed rehabilitation technologies such as virtual reality and augmented reality (AR) have enabled gait and balance training outside clinics. Here, we propose a new method for gait rehabilitation in persons who have had a stroke in which mobile AR technology and a sensor-based motion capture system are combined to provide fine-grained feedback on gait performance in real time. OBJECTIVE The aims of this study were (1) to investigate manipulation of the gait pattern of persons who have had a stroke based on virtual augmentation during overground walking compared to walking without AR performance feedback and (2) to investigate the usability of the AR system. METHODS We developed the ARISE (Augmented Reality for gait Impairments after StrokE) system, in which we combined a development version of HoloLens 2 smart glasses (Microsoft Corporation) with a sensor-based motion capture system. One patient with chronic minor gait impairment poststroke completed clinical gait assessments and an AR parkour course with patient-centered performance gait feedback. The movement kinematics during gait as well as the usability and safety of the system were evaluated. RESULTS The patient changed his gait pattern during AR parkour compared to the pattern observed during the clinical gait assessments. He recognized the virtual objects and ranked the usability of the ARISE system as excellent. In addition, the patient stated that the system would complement his standard gait therapy. Except for the symptom of exhilaration, no adverse events occurred. CONCLUSIONS This project provided the first evidence of gait adaptation during overground walking based on real-time feedback through visual and auditory augmentation. The system has potential to provide gait and balance rehabilitation outside the clinic. This initial investigation of AR rehabilitation may aid the development and investigation of new gait and balance therapies

Data from: Dopamine promotes motor cortex plasticity and motor skill learning via PLC activation

Dopaminergic neurons in the ventral tegmental area, the major midbrain nucleus projecting to the motor cortex, play a key role in motor skill learning and motor cortex synaptic plasticity. Dopamine D1 and D2 receptor antagonists exert parallel effects in the motor system: they impair motor skill learning and reduce long-term potentiation. Traditionally, D1 and D2 receptor modulate adenylyl cyclase activity and cyclic adenosine monophosphate accumulation in opposite directions via different G-proteins and bidirectionally modulate protein kinase A (PKA), leading to distinct physiological and behavioral effects. Here we show that D1 and D2 receptor activity influences motor skill acquisition and long term synaptic potentiation via phospholipase C (PLC) activation in rat primary motor cortex. Learning a new forelimb reaching task is severely impaired in the presence of PLC, but not PKA-inhibitor. Similarly, long term potentiation in motor cortex, a mechanism involved in motor skill learning, is reduced when PLC is inhibited but remains unaffected by the PKA inhibitor. Skill learning deficits and reduced synaptic plasticity caused by dopamine antagonists are prevented by co-administration of a PLC agonist. These results provide evidence for a role of intracellular PLC signaling in motor skill learning and associated cortical synaptic plasticity, challenging the traditional view of bidirectional modulation of PKA by D1 and D2 receptors. These findings reveal a novel and important action of dopamine in motor cortex that might be a future target for selective therapeutic interventions to support learning and recovery of movement resulting from injury and disease

Data from: Dopamine promotes motor cortex plasticity and motor skill learning via PLC activation

Dopaminergic neurons in the ventral tegmental area, the major midbrain nucleus projecting to the motor cortex, play a key role in motor skill learning and motor cortex synaptic plasticity. Dopamine D1 and D2 receptor antagonists exert parallel effects in the motor system: they impair motor skill learning and reduce long-term potentiation. Traditionally, D1 and D2 receptor modulate adenylyl cyclase activity and cyclic adenosine monophosphate accumulation in opposite directions via different G-proteins and bidirectionally modulate protein kinase A (PKA), leading to distinct physiological and behavioral effects. Here we show that D1 and D2 receptor activity influences motor skill acquisition and long term synaptic potentiation via phospholipase C (PLC) activation in rat primary motor cortex. Learning a new forelimb reaching task is severely impaired in the presence of PLC, but not PKA-inhibitor. Similarly, long term potentiation in motor cortex, a mechanism involved in motor skill learning, is reduced when PLC is inhibited but remains unaffected by the PKA inhibitor. Skill learning deficits and reduced synaptic plasticity caused by dopamine antagonists are prevented by co-administration of a PLC agonist. These results provide evidence for a role of intracellular PLC signaling in motor skill learning and associated cortical synaptic plasticity, challenging the traditional view of bidirectional modulation of PKA by D1 and D2 receptors. These findings reveal a novel and important action of dopamine in motor cortex that might be a future target for selective therapeutic interventions to support learning and recovery of movement resulting from injury and disease

Temporal dynamic of Tac1 expression during motor learning.

<p>Levels of Tac1 mRNA within M1 were measured using Real-Time RT-PCR in rats that were trained in a reaching task and related to an activity control at different time points. Tac1 expression was significantly elevated in learning rats seven hours after the training ended in the stage of skill acquisition (training session 1 and 2). This pattern was not observable at a later time-point (training session 6). *: p ≤ 0.05.</p