StairNet: visual recognition of stairs for human-robot locomotion.

Human-robot walking with prosthetic legs and exoskeletons, especially over complex terrains, such as stairs, remains a significant challenge. Egocentric vision has the unique potential to detect the walking environment prior to physical interactions, which can improve transitions to and from stairs. This motivated us to develop the StairNet initiative to support the development of new deep learning models for visual perception of real-world stair environments. In this study, we present a comprehensive overview of the StairNet initiative and key research to date. First, we summarize the development of our large-scale data set with over 515,000 manually labeled images. We then provide a summary and detailed comparison of the performances achieved with different algorithms (i.e., 2D and 3D CNN, hybrid CNN and LSTM, and ViT networks), training methods (i.e., supervised learning with and without temporal data, and semi-supervised learning with unlabeled images), and deployment methods (i.e., mobile and embedded computing), using the StairNet data set. Finally, we discuss the challenges and future directions. To date, our StairNet models have consistently achieved high classification accuracy (i.e., up to 98.8%) with different designs, offering trade-offs between model accuracy and size. When deployed on mobile devices with GPU and NPU accelerators, our deep learning models achieved inference speeds up to 2.8 ms. In comparison, when deployed on our custom-designed CPU-powered smart glasses, our models yielded slower inference speeds of 1.5 s, presenting a trade-off between human-centered design and performance. Overall, the results of numerous experiments presented herein provide consistent evidence that StairNet can be an effective platform to develop and study new deep learning models for visual perception of human-robot walking environments, with an emphasis on stair recognition. This research aims to support the development of next-generation vision-based control systems for robotic prosthetic legs, exoskeletons, and other mobility assistive technologies.

Privacy-protecting behaviours of risk detection in people with dementia using videos.

BACKGROUND: People living with dementia often exhibit behavioural and psychological symptoms of dementia that can put their and others' safety at risk. Existing video surveillance systems in long-term care facilities can be used to monitor such behaviours of risk to alert the staff to prevent potential injuries or death in some cases. However, these behaviours of risk events are heterogeneous and infrequent in comparison to normal events. Moreover, analysing raw videos can also raise privacy concerns. PURPOSE: In this paper, we present two novel privacy-protecting video-based anomaly detection approaches to detect behaviours of risks in people with dementia. METHODS: We either extracted body pose information as skeletons or used semantic segmentation masks to replace multiple humans in the scene with their semantic boundaries. Our work differs from most existing approaches for video anomaly detection that focus on appearance-based features, which can put the privacy of a person at risk and is also susceptible to pixel-based noise, including illumination and viewing direction. We used anonymized videos of normal activities to train customized spatio-temporal convolutional autoencoders and identify behaviours of risk as anomalies. RESULTS: We showed our results on a real-world study conducted in a dementia care unit with patients with dementia, containing approximately 21 h of normal activities data for training and 9 h of data containing normal and behaviours of risk events for testing. We compared our approaches with the original RGB videos and obtained a similar area under the receiver operating characteristic curve performance of 0.807 for the skeleton-based approach and 0.823 for the segmentation mask-based approach. CONCLUSIONS: This is one of the first studies to incorporate privacy for the detection of behaviours of risks in people with dementia. Our research opens up new avenues to reduce injuries in long-term care homes, improve the quality of life of residents, and design privacy-aware approaches for people living in the community.

Researched Apps Used in Dementia Care for People Living With Dementia and Their Informal Caregivers: Systematic Review on App Features, Security, and Usability.

BACKGROUND: Studies have shown that mobile apps have the potential to serve as nonpharmacological interventions for dementia care, improving the quality of life of people living with dementia and their informal caregivers. However, little is known about the needs for and privacy aspects of these mobile apps in dementia care. OBJECTIVE: This review seeks to understand the landscape of existing mobile apps in dementia care for people living with dementia and their caregivers with respect to app features, usability testing, privacy, and security. METHODS: ACM Digital Library, Cochrane Central Register of Controlled Trials, Compendex, Embase, Inspec, Ovid MEDLINE, PsycINFO, and Scopus were searched. Studies were included if they included people with dementia living in the community, their informal caregivers, or both; focused on apps in dementia care using smartphones or tablet computers; and covered usability evaluation of the app. Records were independently screened, and 2 reviewers extracted the data. The Centre for Evidence-Based Medicine critical appraisal tool and Mixed Methods Appraisal Tool were used to assess the risk of bias in the included studies. Thematic synthesis was used, and the findings were summarized and tabulated based on each research aim. RESULTS: Overall, 44 studies were included in this review, with 39 (89%) published after 2015. In total, 50 apps were included in the study, with more apps developed for people living with dementia as end users compared with caregivers. Most studies (27/44, 61%) used tablet computers. The most common app feature was cognitive stimulation. This review presented 9 app usability themes: user interface, physical considerations, screen size, interaction challenges, meeting user needs, lack of self-awareness of app needs, stigma, technological inexperience, and technical support. In total, 5 methods (questionnaires, interviews, observations, logging, and focus groups) were used to evaluate usability. There was little focus on the privacy and security aspects, including data transfer and protection, of mobile apps for people living with dementia. CONCLUSIONS: The limitations of this review include 1 reviewer conducting the full-text screening, its restriction to studies published in English, and the exclusion of apps that lacked empirical usability testing. As a result, there may be an incomplete representation of the available apps in the field of dementia care. However, this review highlights significant concerns related to the usability, privacy, and security of existing mobile apps for people living with dementia and their caregivers. The findings of this review provide a valuable framework to guide app developers and researchers in the areas of privacy policy development, app development strategies, and the importance of conducting thorough usability testing for their apps. By considering these factors, future work in this field can be advanced to enhance the quality and effectiveness of dementia care apps. TRIAL REGISTRATION: PROSPERO CRD42020216141; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=216141. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1159/000514838.

Performance of machine learning algorithms for dementia assessment: impacts of language tasks, recording media, and modalities.

OBJECTIVES: Automatic speech and language assessment methods (SLAMs) can help clinicians assess speech and language impairments associated with dementia in older adults. The basis of any automatic SLAMs is a machine learning (ML) classifier that is trained on participants' speech and language. However, language tasks, recording media, and modalities impact the performance of ML classifiers. Thus, this research has focused on evaluating the effects of the above-mentioned factors on the performance of ML classifiers that can be used for dementia assessment. METHODOLOGY: Our methodology includes the following steps: (1) Collecting speech and language datasets from patients and healthy controls; (2) Using feature engineering methods which include feature extraction methods to extract linguistic and acoustic features and feature selection methods to select most informative features; (3) Training different ML classifiers; and (4) Evaluating the performance of ML classifiers to investigate the impacts of language tasks, recording media, and modalities on dementia assessment. RESULTS: Our results show that (1) the ML classifiers trained with the picture description language task perform better than the classifiers trained with the story recall language task; (2) the data obtained from phone-based recordings improves the performance of ML classifiers compared to data obtained from web-based recordings; and (3) the ML classifiers trained with acoustic features perform better than the classifiers trained with linguistic features. CONCLUSION: This research demonstrates that we can improve the performance of automatic SLAMs as dementia assessment methods if we: (1) Use the picture description task to obtain participants' speech; (2) Collect participants' voices via phone-based recordings; and (3) Train ML classifiers using only acoustic features. Our proposed methodology will help future researchers to investigate the impacts of different factors on the performance of ML classifiers for assessing dementia.

Towards PPG-based anger detection for emotion regulation.

BACKGROUND: Anger dyscontrol is a common issue after traumatic brain injury (TBI). With the growth of wearable physiological sensors, there is new potential to facilitate the rehabilitation of such anger in the context of daily life. This potential, however, depends on how well physiological markers can distinguish changing emotional states and for such markers to generalize to real-world settings. Our study explores how wearable photoplethysmography (PPG), one of the most widely available physiological sensors, could be used detect anger within a heterogeneous population. METHODS: This study collected the TRIEP (Toronto Rehabilitation Institute Emotion-Physiology) dataset, which comprised of 32 individuals (10 TBI), exposed to a variety of elicitation material (film, pictures, self-statements, personal recall), over two day sessions. This complex dataset allowed for exploration into how the emotion-PPG relationship varied over changes in individuals, endogenous/exogenous drivers of emotion, and day-to-day differences. A multi-stage analysis was conducted looking at: (1) times-series visual clustering, (2) discriminative time-interval features of anger, and (3) out-of-sample anger classification. RESULTS: Characteristics of PPG are largely dominated by inter-subject (between individuals) differences first, then intra-subject (day-to-day) changes, before differentiation into emotion. Both TBI and non-TBI individuals showed evidence of linear separable features that could differentiate anger from non-anger classes within time-interval analysis. However, what is more challenging is that these separable features for anger have various degrees of stability across individuals and days. CONCLUSION: This work highlights how there are contextual, non-stationary challenges to the emotion-physiology relationship that must be accounted for before emotion regulation technology can perform in real-world scenarios. It also affirms the need for a larger breadth of emotional sampling when building classification models.

A GPS-Based Framework for Understanding Outdoor Mobility Patterns of Older Adults with Dementia: An Exploratory Study.

INTRODUCTION: An active lifestyle may protect older adults from cognitive decline. Yet, due to the complex nature of outdoor environments, many people living with dementia experience decreased access to outdoor activities. In this context, conceptualizing and measuring outdoor mobility is of great significance. Using the global positioning system (GPS) provides an avenue for capturing the multi-dimensional nature of outdoor mobility. The objective of this study is to develop a comprehensive framework for comparing outdoor mobility patterns of cognitively intact older adults and older adults with dementia using passively collected GPS data. METHODS: A total of 7 people with dementia (PwD) and 8 cognitively intact controls (CTLs), aged 65 years or older, carried a GPS device when travelling outside their homes for 4 weeks. We applied a framework incorporating 12 GPS-based indicators to capture spatial, temporal, and semantic dimensions of outdoor mobility. RESULTS: Despite a small sample size, the application of our mobility framework identified several significant differences between the 2 groups. We found that PwD participated in more medical-related (Cliff's Delta = 0.71, 95% CI: 0.34-1) and fewer sport-related (Cliff's Delta = -0.78, 95% CI: -1 to -0.32) activities compared to the cognitively intact CTLs. Our results also suggested that longer duration of daily walking time (Cliff's Delta = 0.71, 95% CI: 0.148-1) and longer outdoor activities at night, after 8 p.m. (Hedges' g = 1.42, 95% CI: 0.85-1.09), are associated with cognitively intact individuals. CONCLUSION: Based on the proposed framework incorporating 12 GPS-based indicators, we were able to identify several differences in outdoor mobility in PwD compared with cognitively intact CTLs.

Technology-Based Compensation Assessment and Detection of Upper Extremity Activities of Stroke Survivors: Systematic Review.

BACKGROUND: Upper extremity (UE) impairment affects up to 80% of stroke survivors and accounts for most of the rehabilitation after discharge from the hospital release. Compensation, commonly used by stroke survivors during UE rehabilitation, is applied to adapt to the loss of motor function and may impede the rehabilitation process in the long term and lead to new orthopedic problems. Intensive monitoring of compensatory movements is critical for improving the functional outcomes during rehabilitation. OBJECTIVE: This review analyzes how technology-based methods have been applied to assess and detect compensation during stroke UE rehabilitation. METHODS: We conducted a wide database search. All studies were independently screened by 2 reviewers (XW and YF), with a third reviewer (BY) involved in resolving discrepancies. The final included studies were rated according to their level of clinical evidence based on their correlation with clinical scales (with the same tasks or the same evaluation criteria). One reviewer (XW) extracted data on publication, demographic information, compensation types, sensors used for compensation assessment, compensation measurements, and statistical or artificial intelligence methods. Accuracy was checked by another reviewer (YF). Four research questions were presented. For each question, the data were synthesized and tabulated, and a descriptive summary of the findings was provided. The data were synthesized and tabulated based on each research question. RESULTS: A total of 72 studies were included in this review. In all, 2 types of compensation were identified: disuse of the affected upper limb and awkward use of the affected upper limb to adjust for limited strength, mobility, and motor control. Various models and quantitative measurements have been proposed to characterize compensation. Body-worn technology (25/72, 35% studies) was the most used sensor technology to assess compensation, followed by marker-based motion capture system (24/72, 33% studies) and marker-free vision sensor technology (16/72, 22% studies). Most studies (56/72, 78% studies) used statistical methods for compensation assessment, whereas heterogeneous machine learning algorithms (15/72, 21% studies) were also applied for automatic detection of compensatory movements and postures. CONCLUSIONS: This systematic review provides insights for future research on technology-based compensation assessment and detection in stroke UE rehabilitation. Technology-based compensation assessment and detection have the capacity to augment rehabilitation independent of the constant care of therapists. The drawbacks of each sensor in compensation assessment and detection are discussed, and future research could focus on methods to overcome these disadvantages. It is advised that open data together with multilabel classification algorithms or deep learning algorithms could benefit from automatic real time compensation detection. It is also recommended that technology-based compensation predictions be explored.

The Development and Concurrent Validity of a Multi-Sensor-Based Frailty Toolkit for In-Home Frailty Assessment.

Early identification of frailty is crucial to prevent or reverse its progression but faces challenges due to frailty's insidious onset. Monitoring behavioral changes in real life may offer opportunities for the early identification of frailty before clinical visits. This study presented a sensor-based system that used heterogeneous sensors and cloud technologies to monitor behavioral and physical signs of frailty from home settings. We aimed to validate the concurrent validity of the sensor measurements. The sensor system consisted of multiple types of ambient sensors, a smart speaker, and a smart weight scale. The selection of these sensors was based on behavioral and physical signs associated with frailty. Older adults' perspectives were also included in the system design. The sensor system prototype was tested in a simulated home lab environment with nine young, healthy participants. Cohen's Kappa and Bland−Altman Plot were used to evaluate the agreements between the sensor and ground truth measurements. Excellent concurrent validity was achieved for all sensors except for the smart weight scale. The bivariate correlation between the smart and traditional weight scales showed a strong, positive correlation between the two measurements (r = 0.942, n = 24, p < 0.001). Overall, this work showed that the Frailty Toolkit (FT) is reliable for monitoring physical and behavioral signs of frailty in home settings.

Bringing the "Place" to Life-Space in Gerontology Research.

Understanding older adults' relationships with their environments and the way this relationship evolves over time have been increasingly acknowledged in gerontological research. This relationship is often measured in terms of life-space, defined as the spatial area through which a person moves within a specific period of time. Life-space is traditionally reported using questionnaires or travel diaries and is, thus, subject to inaccuracies. More recently, studies are using a global positioning system to accurately measure life-space. Although life-space provides useful insights into older adults' relationships with their environment, it does not capture the inherent complexities of environmental exposures. In the fields of travel behaviour and health geography, a substantial amount of research has looked at people's spatial behaviour using the notion of "Activity Space," allowing for increasing sophistication in understanding older adults' experience of their environment. This manuscript discusses developments and directions for extending the life-space framework in environmental gerontology by drawing on the advancements in the activity space framework.

Dementia Care Apps for People with Dementia and Informal Caregivers: A Systematic Review Protocol.

Dementia drastically impacts the quality of life (QOL) of both people living with dementia (PLwD) and their family caregivers. As dementia progresses and care needs escalate, the likelihood of institutionalization is increased, which is counter to the wishes of the majority of older adults and their family members. Dementia care apps can provide critical support and have the potential to improve the QOL of both PLwD and their family caregivers and reduce perceived caregivers' burden. However, there is a lack of understanding of the needs of both PLwD and their family caregivers related to dementia care apps. There is also a gap in understanding the privacy concerns in relation to the apps among older adults with dementia and their caregivers. As such, the main aims of this systematic review are to understand the landscape of dementia mobile apps targeting PLwD and their caregivers with respect to the features of the apps, usability testing, and the privacy and security aspects of the app from the perspective of both app developers/researchers and the end users (PLwD and family caregivers who provide care of PLwD). Extensive databases, including ACM Digital Library, Cochrane Central Register of Controlled Trials, Compendex, Embase, Inspec, Ovid MEDLINE(R) Daily, Proquest Dissertations and These Global, PsycINFO, and Scopus, have been searched. All searches are from the inception of the databases. All peer-reviewed studies and articles written in the English language are included. Two reviewers will independently screen and select the studies with the involvement of a third reviewer for disagreements. Data will be abstracted using a custom data extraction form that is made based on the research questions. Critical Appraisal Skills Programme (CASP) checklists will be used to assess the study quality. As the first review of its kind, the findings from this review will provide valuable insights related to the needs of the dementia care apps for both PLwD and their family caregivers. The review will be relevant to health providers who are interested in using technologies to promote the independence of PLwD and reduce the stress experienced from caregivers of PLwD. The review will also serve as a guide to app developers and researchers to design usable and acceptable apps. In addition, the review will provide critical knowledge of the privacy and security features of the app to reveal the valid concerns from the end users and thus help with the uptake and adoption of the dementia care apps.

Influence of Multiple Sclerosis on Spatiotemporal Gait Parameters: A Systematic Review and Meta-Regression.

OBJECTIVE: To quantify the effect of multiple sclerosis (MS) on spatiotemporal gait characteristics accounting for disability severity and fall classification. DATA SOURCES: MEDLINE (1946-August 2018), Allied and Complementary Medicine Database (1985-2018 August), and PsycINFO (1806-August 2018) were searched for terms on MS and gait. STUDY SELECTION: Dual independent screening was conducted to identify observational, cross-sectional studies that compared adults with MS grouped according to Expanded Disability Status Scale (EDSS) level or fall history, reported on spatiotemporal gait characteristics, and were published in English. The search retrieved 5891 results, of which 12 studies satisfied the inclusion criteria. DATA EXTRACTION: Two authors worked independently to extract and verify data on publication details, study methodology, participant characteristics, gait outcomes, conclusions, and limitations. Risk of bias was assessed using the QualSyst critical appraisal tool. A random-effects meta-regression and meta-analysis were conducted on pooled data. DATA SYNTHESIS: All studies received quality ratings of very good to excellent and collectively examined 1513 individuals with MS. With every 1-point increase in EDSS, significant changes (P<.05) were observed in gait speed (-0.12 m/s; 95% confidence interval (CI), 0.08-0.15), step length (-0.04 m; 95% CI, 0.03-0.05), step time (+0.04 seconds; 95% CI, 0.02-0.06), step time variability (+0.009 seconds; 95% CI, 0.003-0.016), stride time (+0.08 seconds; 95% CI, 0.03-0.12), cadence (-4.4 steps per minute; 95% CI, 2.3-6.4), stance phase duration (+0.8% gait cycle; 95% CI, 0.1-1.5), and double support time (+3.5% gait cycle; 95% CI, 1.5-5.4). Recent fallers exhibited an 18% (95% CI, 13%-23%) reduction in gait speed compared with nonfallers (P<.001). CONCLUSIONS: This review provides the most accurate reference values to-date that can be used to assess the effectiveness of MS gait training programs and therapeutic techniques for individuals who differ on disability severity and fall classification. Some gait adaptations could be part of adopting a more cautious gait strategy and should be factored into the design of future interventions.

Attitudes and perspectives of older adults on technologies for assessing frailty in home settings: a focus group study.

BACKGROUND: The rapid development of technology such as sensors and artificial intelligence in recent years enables monitoring frailty criteria to assess frailty early and accurately from a remote location such as a home. However, research shows technologies being abandoned or rejected by users due to a lack of compatibility and consumer involvement in selecting their assistive technology devices. This study aims to understand older adults' perceptions and preferences of technologies that can potentially assess frailty at home. METHODS: This study collected qualitative data through focus group meetings with 15 participants ages 65 and older. Researchers asked participants questions to achieve the goal of understanding their attitudes on the technologies. These questions include (1) the concerns or barriers of installing and using the presented technology in daily life at home, (2) the reasons participants like or dislike a particular technology, (3) what makes a specific technology more acceptable, and (4) participants' preferences in choosing technologies. Data were transcribed, coded and categorized, and finally synthesized to understand the attitudes towards presented technologies. RESULTS: Three focus group sessions were conducted with five participants in each session. In the findings, the attitudes and perspectives of participants on the technologies for assessing frailty were categorized into four themes: (A) general attitude towards using the technologies, (B) conditions for accepting certain technologies, (C) existing living habits or patterns related to using the technologies, and (D) constructive suggestions related to the technologies. CONCLUSIONS: Participants generally had positive attitudes towards allowing the technologies to be installed and used at their homes. They would accept some technologies if used under certain conditions. However, questions and concerns remain, such as concerns about privacy, functionality, and aesthetics. The study also found that older adults' living habits or patterns could affect the design and use of technology. Lastly, many valuable suggestions have been made by participants. These perspectives and insights can help improve the design and adoption of home-based frailty assessment technologies among older adults.

Sex and gender differences in technology needs and preferences among informal caregivers of persons with dementia.

BACKGROUND: Dementia is a major public health concern associated with significant caregiver demands and there are technologies available to assist with caregiving. However, there is a paucity of information on caregiver needs and preferences for these technologies, particularly from a sex and gender perspective. To address this gap in research, the objectives of this study are to examine (1) the knowledge of technology, (2) perceived usefulness of technology, (3) feature preferences when installing and using technology and (4) sex and gender influences on technology needs and preferences among family caregivers of persons with dementia (PWD) across North America. METHODS: A secondary analysis was conducted on an existing cross-sectional survey with family caregivers of PWDs. Respondents were recruited through the Alzheimer Society of Canada, the Victorian Order of Nurses and Adult Day Programs and other Canadian health care provision institutes. Descriptive statistics, bivariate and multivariate analyses were used to describe the study sample, uncover differences between male and female caregivers and examine sex and gender influences on caregivers' technology needs and preferences. RESULTS: A total of 381 eligible responses were received over a nine month data collection period. The majority of respondents did not know much about and never used any technologies to assist with caregiving. "Being easy to install", "easy to learn how to use" and "cost" were identified as the most important features when purchasing and setting up technology, while "reliability" was identified as the most important feature when using technology. Most respondents were willing to pay up to $500 to acquire individual technologies. Controlling for other socio-demographic variables, female respondents were more likely to have some or more knowledge about technology for caregiving while male respondents were more willing to pay higher amounts for these technologies compared to their female counterparts. CONCLUSIONS: As one of the first studies of its kind, our findings represent a step towards the incorporation of sex and gender considerations such as cost and reliability in technology design and promotion for caregivers. Future efforts are warranted to establish an in-depth understanding of sex and gender influences in relation to other social and environmental factors.

Hand Extension Robot Orthosis (HERO) Grip Glove: enabling independence amongst persons with severe hand impairments after stroke.

BACKGROUND: The Hand Extension Robot Orthosis (HERO) Grip Glove was iteratively designed to meet requests from therapists and persons after a stroke who have severe hand impairment to create a device that extends all five fingers, enhances grip strength and is portable, lightweight, easy to put on, comfortable and affordable. METHODS: Eleven persons who have minimal or no active finger extension (Chedoke McMaster Stage of Hand 1-4) post-stroke were recruited to evaluate how well they could perform activities of daily living and finger function assessments with and without wearing the HERO Grip Glove. RESULTS: The 11 participants showed statistically significant improvements (p < 0.01), while wearing the HERO Grip Glove, in the water bottle grasp and manipulation task (increase of 2.3 points, SD 1.2, scored using the Chedoke Hand and Arm Inventory scale from 1 to 7) and in index finger extension (increase of 147o, SD 44) and range of motion (increase of 145o, SD 36). The HERO Grip Glove provided 12.7 N (SD 8.9 N) of grip force and 11.0 N (SD 4.8) of pinch force to their affected hands, which enabled those without grip strength to grasp and manipulate blocks, a fork and a water bottle, as well as write with a pen. The participants were 'more or less satisfied' with the HERO Grip Glove as an assistive device (average of 3.3 out of 5 on the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 Scale). The highest satisfaction scores were given for safety and security (4.6) and ease of use (3.8) and the lowest satisfaction scores were given for ease of donning (2.3), which required under 5 min with assistance. The most common requests were for greater grip strength and a smaller glove size for small hands. CONCLUSIONS: The HERO Grip Glove is a safe and effective tool for enabling persons with a stroke that have severe hand impairment to incorporate their affected hand into activities of daily living, which may motivate greater use of the affected upper extremity in daily life to stimulate neuromuscular recovery.

Oral care practices of long-term care home residents and caregivers: Secondary analysis of observational video recordings.

AIMS AND OBJECTIVES: To describe the proportion of toothbrushing task steps, long-term care residents had an opportunity to complete; the duration and quality of toothbrushing by both residents and caregivers; and the feedback caregivers provided. BACKGROUND: Poor oral health is widespread among older adults in long-term care homes; however, little is known about their actual oral health practices. DESIGN: Secondary analysis of video recordings. METHODS: A total of 58 video-recorded sessions were analysed from two long-term care homes in Canada. Eligible residents had at least one natural tooth, required oral care assistance, had Alzheimer's disease and understood English. Eligible caregivers spoke English and had worked for at least 1 year with people with dementia. Toothbrushing success was identified by the resident's participation in, and completion of, nine toothbrushing steps. Total time spent brushing teeth was calculated by summing the duration of time spent brushing teeth. Quality was described by time spent brushing the facial versus the lingual or occlusal surfaces. Caregiver verbal feedback was pulled from transcripts and analysed using content analysis. STROBE guidelines were used in reporting this study. RESULTS: The two step residents most frequently completed or attempted were brushing their teeth (77% complete, 7% attempt) and rinsing their mouth (86% complete, 2% attempt). The average time spent brushing teeth was 60.33 s (SD = 35.15). In 66% of observed videos, toothbrushing occurred only on the facial tooth surfaces, with no time spent brushing the lingual or occlusal surfaces. CONCLUSION: Caregivers are supporting residents to independently complete toothbrushing; however, the duration and quality of toothbrushing are not sufficient to ensure optimal oral health. RELEVANCE TO CLINICAL PRACTICE: Clear, detailed guidelines are required to ensure adequate oral care for long-term care residents. Staff need to be aware that all surfaces should be brushed to ensure proper oral health.

Technology and Dementia: The Future is Now.

BACKGROUND: Technology has multiple potential applications to dementia from diagnosis and assessment to care delivery and supporting ageing in place. OBJECTIVES: To summarise key areas of technology development in dementia and identify future directions and implications. METHOD: Members of the US Alzheimer's Association Technology Professional Interest Area involved in delivering the annual pre-conference summarised existing knowledge on current and future technology developments in dementia. RESULTS: The main domains of technology development are as follows: (i) diagnosis, assessment and monitoring, (ii) maintenance of functioning, (iii) leisure and activity, (iv) caregiving and management. CONCLUSIONS: The pace of technology development requires urgent policy, funding and practice change, away from a narrow medical approach, to a holistic model that facilitates future risk reduction and prevention strategies, enables earlier detection and supports implementation at scale for a meaningful and fulfilling life with dementia.

Challenges in Collecting Big Data in A Clinical Environment with Vulnerable Population: Lessons Learned from A Study Using A Multi-modal Sensors Platform.

Agitation is one of the most common behavioural and psychological symptoms in people living with dementia (PLwD). This behaviour can cause tremendous stress and anxiety on family caregivers and healthcare providers. Direct observation of PLwD is the traditional way to measure episodes of agitation. However, this method is subjective, bias-prone and timeconsuming. Importantly, it does not predict the onset of the agitation. Therefore, there is a need to develop a continuous monitoring system that can detect and/or predict the onset of agitation. In this study, a multi-modal sensor platform with video cameras, motion and door sensors, wristbands and pressure mats were set up in a hospital-based dementia behavioural care unit to develop a predictive system to identify the onset of agitation. The research team faced several barriers in the development and initiation of the study, namely addressing concerns about the study ethics, logistics and costs of study activities, device design for PLwD and limitations of its use in the hospital. In this paper, the strategies and methodologies that were implemented to address these challenges are discussed for consideration by future researchers who will conduct similar studies in a hospital setting.

"A Chance to Try": Exploring the Clinical Utility of Shared-Control Teleoperation for Powered Wheelchair Assessment and Training.

IMPORTANCE: Powered wheelchairs provide independence for people with mobility impairments; however, current training practices may not meet the needs of those with cognitive impairments. Shared-control teleoperation may have utility in a clinical setting when developing training suited to this population. OBJECTIVE: To explore the clinical utility of a shared-control teleoperation device for powered wheelchair assessment and training. DESIGN: In this qualitative study, we used two sequential semistructured interviews conducted a minimum of 2 wk apart. Thematic analyses were used with member checking, reflexive journaling, and triangulation of researchers to establish trustworthiness of the data. SETTING: Rehabilitation center and residential care and community settings. PARTICIPANTS: Using purposive sampling, we recruited occupational therapists and physical therapists who were mostly female and who had a range of practice experience. RESULTS: Fifteen participants were interviewed, and two primary themes were identified: (1) "A big enabler" described how shared control provides opportunities to train people who may otherwise be denied powered mobility, and (2) "changing the learner experience" described how shared control may promote success in skill development through an alternative learning experience. CONCLUSIONS AND RELEVANCE: Shared-control technology may have the potential to broaden the scope of therapeutic intervention by reducing risk to the driver and others in the environment and by facilitating alternative training approaches. WHAT THIS ARTICLE ADDS: Technological advances that allow more control over a powered wheelchair by a clinician, known as shared control, may provide learning opportunities for people who are otherwise denied access to powered mobility. Shared control may also allow the use of new instructional techniques, increase safety in the training process, and reduce anxiety associated with learning.

The contrasting role of technology as both supportive and hindering in the everyday lives of people with mild cognitive deficits: a focus group study.

BACKGROUND: It is well known that people with mild cognitive deficits face challenges when performing complex everyday activities, and that the use of technology has become increasingly interwoven with everyday activities. However, less is known of how technology might be involved, either as a support or hindrance, in different areas of everyday life and of the environments where challenges appear. The aim of this study was to investigate the areas of concern where persons with cognitive deficits meet challenges in everyday life, in what environments these challenges appear and how technology might be involved as part of the challenge and/or the solution to the challenge. METHODS: Data were gathered through four focus group interviews with participants that live with cognitive deficits or cohabit with a person with cognitive deficits, plus health professionals and researchers in the field. Data were transcribed, coded and categorized, and finally synthesized to trace out the involvement of technology. RESULTS: Five areas of concern in everyday life were identified as offering challenges to persons with cognitive deficits: A) Managing personal finances, B) Getting around, C) Meeting family and friends, D) Engaging with culture and media and, E) Doing everyday chores. Findings showed that the involvement of technology in everyday activities was often contrastive. It could be hindering and evoke stress, or it could bring about feelings of control; that is, being a part of the solution. The involvement of technology was especially obvious in challenges linked to Managing personal finances, which is a crucial necessity in many everyday activities. In contrast, technology was least obviously involved in the area Socializing with family and friends. CONCLUSIONS: The findings imply that technology used for orientation and managing finances, often used outside home, would benefit from being further developed in order to be more supportive; i.e. accessible and usable. To make a positive change for many people, the ideas of inclusive design fit well for this purpose and would contribute to an age-friendly society.

Changes in working memory performance in youth following concussion.

OBJECTIVE: The purpose of this study was to compare the working memory (WM) performance pre- and post-concussion, and investigate the relationships between performance changes and characteristics such as self-reported symptom scores, number of days post-injury and age at injury in 10-14-year-old youth. METHODS: Twenty-one youth (17 males) aged 10-14 years recruited from the community completed verbal and non-verbal WM tasks pre- and post-concussion. Performance was measured using accuracy and performance errors (false alarms and misses). Pre- and post-tests were compared using a Wilcoxon signed rank test, and effect size was determined using matched-pairs rank biserial correlation. RESULTS: Comparisons showed lower verbal WM accuracy at post-test, greater verbal and non-verbal WM false alarm errors at post-test, and greater verbal WM miss errors at post-test (all r ≥ 0.30). Correlations between performance and characteristics revealed associations between younger youth and lower non-verbal WM accuracy and more false alarms at post-test, as well as an association among non-verbal WM miss errors, higher PCS scores and fewer days since injury at post-test. CONCLUSIONS: The current study found lower WM performance in youth following concussion. Furthermore, the findings suggest that false alarm errors may be a useful screening measure acutely post-concussion when assessing WM performance in youth.