Pose2Gait: Extracting Gait Features from Monocular Video of Individuals with Dementia

Video-based ambient monitoring of gait for older adults with dementia has the potential to detect negative changes in health and allow clinicians and caregivers to intervene early to prevent falls or hospitalizations. Computer vision-based pose tracking models can process video data automatically and extract joint locations; however, publicly available models are not optimized for gait analysis on older adults or clinical populations. In this work we train a deep neural network to map from a two dimensional pose sequence, extracted from a video of an individual walking down a hallway toward a wall-mounted camera, to a set of three-dimensional spatiotemporal gait features averaged over the walking sequence. The data of individuals with dementia used in this work was captured at two sites using a wall-mounted system to collect the video and depth information used to train and evaluate our model. Our Pose2Gait model is able to extract velocity and step length values from the video that are correlated with the features from the depth camera, with Spearman's correlation coefficients of .83 and .60 respectively, showing that three dimensional spatiotemporal features can be predicted from monocular video. Future work remains to improve the accuracy of other features, such as step time and step width, and test the utility of the predicted values for detecting meaningful changes in gait during longitudinal ambient monitoring.Comment: 14 pages, 3 figures. Code is available at https://github.com/TaatiTeam/pose2gait_public . To be published at the Ambient Intelligence for Health Care Workshop at MICCAI 202

Undersampling and Cumulative Class Re-decision Methods to Improve Detection of Agitation in People with Dementia

Agitation is one of the most prevalent symptoms in people with dementia (PwD) that can place themselves and the caregiver's safety at risk. Developing objective agitation detection approaches is important to support health and safety of PwD living in a residential setting. In a previous study, we collected multimodal wearable sensor data from 17 participants for 600 days and developed machine learning models for predicting agitation in one-minute windows. However, there are significant limitations in the dataset, such as imbalance problem and potential imprecise labels as the occurrence of agitation is much rarer in comparison to the normal behaviours. In this paper, we first implement different undersampling methods to eliminate the imbalance problem, and come to the conclusion that only 20\% of normal behaviour data are adequate to train a competitive agitation detection model. Then, we design a weighted undersampling method to evaluate the manual labeling mechanism given the ambiguous time interval (ATI) assumption. After that, the postprocessing method of cumulative class re-decision (CCR) is proposed based on the historical sequential information and continuity characteristic of agitation, improving the decision-making performance for the potential application of agitation detection system. The results show that a combination of undersampling and CCR improves F1-score and other metrics to varying degrees with less training time and data used, and inspires a way to find the potential range of optimal threshold reference for clinical purpose.Comment: 19 pages, 8 figure

Comparative safety of chronic versus intermittent benzodiazepine prescribing in older adults : a population-based cohort study

BACKGROUND: Benzodiazepine treatment recommendations for older adults differ markedly between guidelines, especially their advice on the acceptability of long-term use. AIMS: Using population-based data we compared risks associated with chronic versus intermittent benzodiazepine usage in older adults. The primary outcome was falls resulting in hospital/emergency department visits. METHODS: We undertook a retrospective population-based cohort study using linked healthcare databases in adults aged ⩾ 66 years in Ontario, Canada, with a first prescription for benzodiazepines. Chronic and intermittent benzodiazepine users, based on the 180 days from index prescription, were matched (1:2 ratio) by sex, age and propensity score, then followed for up to 360 days. Hazard ratios (HRs) for outcomes were calculated from Cox regression models. RESULTS: A total of 57,041 chronic and 113,839 matched intermittent users were included. Hospitalization/emergency department visits for falls occurred during follow up in 4.6% chronic versus 3.2% intermittent users (HR = 1.13, 95% confidence interval (CI): 1.08 to 1.19; p < 0.0001). There were significant excess risks in chronic users for most secondary outcomes: hip fractures, hospitalizations/emergency department visits, long-term care admission and death, but not wrist fractures. Adjustment for benzodiazepine dosage had minimal impact on HRs. CONCLUSION: Our study demonstrates evidence of significant excess risks associated with chronic benzodiazepine use compared to intermittent use. The excess risks may inform decision-making by older adults and clinicians about whether short- or long-term benzodiazepine use is a reasonable option for symptom management

Prevalence, causes, and consequences of moral distress in healthcare providers caring for people living with dementia in long-term care during a pandemic

Healthcare providers caring for people living with dementia may experience moral distress when faced with ethically challenging situations, such as the inability to provide care that is consistent with their values. The COVID-19 pandemic produced conditions in long-term care homes (LTCHs) that could potentially contribute to moral distress. We conducted an online survey to examine changes in moral distress during the pandemic, its contributing factors and correlates, and its impact on the well-being of LTCH staff. Survey participants (n=227) working in LTCHs across Ontario, Canada were recruited through provincial LTCH organizations. Using a Bayesian approach, we examined the association between moral distress and staff demographics and roles, and characteristics of the LTCH. We performed a qualitative analysis of the survey's free-text responses. More than 80% of LTCH healthcare providers working with people with dementia reported an increase in moral distress since the start of the pandemic. There was no difference in the severity of distress by age, sex, role, or years of experience. The most common factors associated with moral distress were lack of activities and family visits, insufficient staffing and high turnover, and having to follow policies and procedures that were perceived to harm residents with dementia. At least two-thirds of respondents reported feelings of physical exhaustion, sadness/anxiety, frustration, powerlessness, and guilt due to the moral distress experienced during the pandemic. Respondents working in not-for-profit or municipal homes reported less sadness/anxiety and feelings of not wanting to go to work than those in for-profit homes. Front-line staff were more likely to report not wanting to work than those in management or administrative positions. Overall, we found that increases in moral distress during the pandemic negatively affected the well-being of healthcare providers in LTCHs, with preliminary evidence suggesting that individual and systemic factors may intensify the negative effect

Barriers and facilitators to person-centred infection prevention and control: results of a survey about the Dementia Isolation Toolkit

Objectives: People working in long-term care homes (LTCH) face difficult decisions balancing the risk of spread of infection with the hardship that infection control and prevention (ICP) measures put on residents. The Dementia Isolation Toolkit (DIT) was developed to address the gap in ethical guidance on how to safely and effectively isolate people living with dementia while supporting their personhood. In this study, we report the results of a survey of LTCH staff on barriers and facilitators regarding isolating residents, and on the use and impact of the DIT. Design: Online survey. Setting and Participants: Participants (n=208) were staff working on-site in LTCH in Ontario, Canada since March 1, 2020, with direct or indirect experience with the isolation of LTCH resi-dents. Methods: LTCH staff were recruited through provincial LTCH organizations, social media, and the DIT website. Survey results were summarized, and three groups compared, those: 1) unfamiliar with, 2) familiar with, and 3) users of the DIT. Results: 61% of respondents identified distress of LTCH staff about the harmful effects of isola-tion on residents as a major barrier to effective isolation. Facilitators for isolation included delivery of 1:1 activity in the resident’s room (81%) and designating essential caregivers to provide support (67%). Almost all respondents (84%) reported an increase in moral distress. DIT users were less likely to report an impact of moral distress on job satisfaction (OR 0.41, 95% CI 0.19-0.87) with 48% of users reporting it was helpful in reducing their level of distress. Conclusions and Implications: Isolation as an ICP measure in LTCH environments creates mor-al distress in staff which is a barrier to its effectiveness. ICP guidance to LTCH would be strength-ened with the inclusion of a dementia-specific ethical framework that addresses how to minimize the harms of isolation on both residents and staff

Harmonizing data on correlates of sleep in children within and across neurodevelopmental disorders: lessons learned from an Ontario Brain Institute cross-program collaboration

There is an increasing desire to study neurodevelopmental disorders (NDDs) together to understand commonalities to develop generic health promotion strategies and improve clinical treatment. Common data elements (CDEs) collected across studies involving children with NDDs afford an opportunity to answer clinically meaningful questions. We undertook a retrospective, secondary analysis of data pertaining to sleep in children with different NDDs collected through various research studies. The objective of this paper is to share lessons learned for data management, collation, and harmonization from a sleep study in children within and across NDDs from large, collaborative research networks in the Ontario Brain Institute (OBI). Three collaborative research networks contributed demographic data and data pertaining to sleep, internalizing symptoms, health-related quality of life, and severity of disorder for children with six different NDDs: autism spectrum disorder; attention deficit/hyperactivity disorder; obsessive compulsive disorder; intellectual disability; cerebral palsy; and epilepsy. Procedures for data harmonization, derivations, and merging were shared and examples pertaining to severity of disorder and sleep disturbances were described in detail. Important lessons emerged from data harmonizing procedures: prioritizing the collection of CDEs to ensure data completeness; ensuring unprocessed data are uploaded for harmonization in order to facilitate timely analytic procedures; the value of maintaining variable naming that is consistent with data dictionaries at time of project validation; and the value of regular meetings with the research networks to discuss and overcome challenges with data harmonization. Buy-in from all research networks involved at study inception and oversight from a centralized infrastructure (OBI) identified the importance of collaboration to collect CDEs and facilitate data harmonization to improve outcomes for children with NDDs

An evolutionary and functional analysis of the extended B7 family of costimulatory molecules

T cell activation requires antigen-independent costimulatory signals induced by the interaction of costimulatory molecules on an antigen-presenting cell (APC) with their receptors on the T cell. CD28 and CTLA-4 are both expressed at the T cell surface and mediate positive and negative signals respectively when engaged by their APCexpressed ligands, B7-1 and B7-2. This thesis establishes that the mouse orthologue of a third CD28-like molecule, ICOS, does not bind to mouse B7-1 and B7-2. To find a B7-like ICOS ligand, the sequence motifs defining the B7 family of molecules were established and used to identify new and distant family members in both the mouse and human. In the process, several new B7 family genes were found, including a mouse ligand for ICOS, called LICOS. The evolution of the B7 family was examined via phylogenetic analysis and linked to that of the human major histocompatibility complex. Cloning and preliminary characterisation of the new genes confirmed their relationship to B7 molecules, and demonstrated their expression in tissues of immunological interest. The original members of the B7 family, B7-1 and B7-2, have been considered to have essentially equivalent binding properties. This view is challenged in this thesis through the analysis of the affinities and kinetics of the mouse B7 interactions using surface plasmon resonance-based methods. B7-1 and B7-2 were found to have different binding properties, including distinct preferences for binding to CD28 or CTLA-4. The conservation of these properties in the mouse underscores the significance of a new view of this system established in recent studies of the human orthologues. Finally, the focus is shifting toward understanding the nature of these interactions at the T cell/APC interface. To initiate work in this area, a new bioluminescence-based assay was evaluated and used to characterise the selfassociation of B7-1 at the cell surface.</p

Uses, Barriers and Facilitators of Quantitative Gait Analysis Technologies in the Clinical Care of Adults: A Scoping Review Protocol

This is a scoping review protocol registration. Quantitative gait analysis can support clinical decision-making by helping inform diagnoses, characterize gait impairments, and monitor treatment efficacy. This analysis is performed using wearable sensors, non-wearable sensors, or a combination of both sensors, however, has not been widely adopted in clinical practice. To assist with the integration of quantitative gait analysis technologies we require an understanding of how they are being used and what acts as barriers and facilitators to their clinical adoption. As there are many types of quantitative gait analysis technologies, their uses, barriers, and facilitators are unique to each respective technology, clinical context, and patient population. The objective of this proposed scoping review is thus to synthesize the uses, barriers, and facilitators of various quantitative gait analysis technologies in the clinical care of adults. The goal of this review is to assist researchers in developing and implementing quantitative gait analysis technologies and provide knowledge to clinicians on how these technologies can be used in their practice