Fall prevention intervention technologies: A conceptual framework and survey of the state of the art

In recent years, an ever increasing range of technology-based applications have been developed with the goal of assisting in the delivery of more effective and efficient fall prevention interventions. Whilst there have been a number of studies that have surveyed technologies for a particular sub-domain of fall prevention, there is no existing research which surveys the full spectrum of falls prevention interventions and characterises the range of technologies that have augmented this landscape. This study presents a conceptual framework and survey of the state of the art of technology-based fall prevention systems which is derived from a systematic template analysis of studies presented in contemporary research literature. The framework proposes four broad categories of fall prevention intervention system: Pre-fall prevention; Post-fall prevention; Fall injury prevention; Cross-fall prevention. Other categories include, Application type, Technology deployment platform, Information sources, Deployment environment, User interface type, and Collaborative function. After presenting the conceptual framework, a detailed survey of the state of the art is presented as a function of the proposed framework. A number of research challenges emerge as a result of surveying the research literature, which include a need for: new systems that focus on overcoming extrinsic falls risk factors; systems that support the environmental risk assessment process; systems that enable patients and practitioners to develop more collaborative relationships and engage in shared decision making during falls risk assessment and prevention activities. In response to these challenges, recommendations and future research directions are proposed to overcome each respective challenge.The Royal Society, grant Ref: RG13082

Measuring health status using wearable devices for patients undergoing radical cystectomy

Wearable devices (WDs) are an untapped resource for measuring patient health status during the peri-operative period. The overarching aim of this thesis is to explore the potential for WDs to be used in the clinical setting for patients undergoing radical cystectomy (RC) for bladder cancer. The lack of consensus regarding the optimal approach for RC presents an opportunity to design an RCT comparing open (ORC) and robotic (RARC) RC, in which a wearable device sub-study can be embedded. While the intracorporeal Robotic vs Open Cystectomy (iROC) trial will address the comparison between ORC and RARC, my thesis focuses on exploring the clinical utility of WDs. I present the results of a systematic review of RCTs comparing ORC and RARC. Meta-analysis shows no significant difference in peri-operative and oncological outcomes between ORC and RARC. Additionally, I systematically review healthcare studies using WDs and highlight the findings, device choices and device metrics used. Step-count is the most frequently collected WD metric, and chronic health conditions are the focus of majority of studies. Findings from these systematic reviews guided the design of the iROC trial protocol. I present the pre-planned interim analysis of the iROC trial, and explore associations between WD data and pre-operative health measures including cardiopulmonary exercise testing (CPET). Step-count correlates with the CPET variables (p < 0.01) routinely used to risk-stratify patients undergoing RC, and is the only predictor of major complications following RC in a logistic regression model. Finally, I evaluate recovery of baseline step-count at three months post-operatively as a predictor of overall survival. Applying a threshold of 50% recovery at 3 months, step-count predicts one-year survival to a sensitivity and specificity of 100% and 93% respectively. My findings highlight the potential of WDs in peri-operative care, and my post-doctoral work will progress this work further

The effectiveness of interventions to improve the care and management of people with dementia in general hospitals: a systematic review

Background: People with dementia are at greater risk of being admitted to hospital where care may not be tailored to their needs. Interventions improving care and management are vital. Aim: Assess the effectiveness of interventions designed to improve the care and management of people with dementia in hospital. Method: Six medical and trial registry, and grey literature databases were searched (1999‐1998/2018). Search terms included “Dementia,” “Hospital,” and “Intervention” and limited to experimental designs. Interventions designed to improve the care and management of people with dementia in the general hospital setting were examined. Outcomes included behavioural and psychological symptoms of dementia (BPSD), psychosocial, clinical, staff knowledge, and length of hospital stay. The CASP tools, Cochrane risk of bias tool, and GRADE system assessed methodological quality and certainty of evidence. Results: 9003 unique citations were identified; 24 studies were included. Studies were limited in study design and their conduct was at a risk of bias. There is very low‐quality evidence that multisensory behaviour therapy reduces BPSD. There is low‐quality evidence that a multidisciplinary programme reduces postoperative complications and that robot‐assisted therapy, music therapy, multimodal‐comprehensive care, person‐centred care, and family‐centred function‐focused care interventions improved staff knowledge, competence, efficacy, and communication. No studies reported reduced length of stay. Conclusions: Whilst we found that these interventions improved the care and management of people with dementia in hospital, it was low‐ to very low‐quality evidence. New clinical recommendations cannot be made based on current evidence, and robust trial designs are necessary to inform evidence‐based care

Sensing Technology to Monitor Behavioral and Psychological Symptoms and to Assess Treatment Response in People With Dementia. A Systematic Review

Background: The prevalence of dementia is expected to rapidly increase in the next decades, warranting innovative solutions improving diagnostics, monitoring and resource utilization to facilitate smart housing and living in the nursing home. This systematic review presents a synthesis of research on sensing technology to assess behavioral and psychological symptoms and to monitor treatment response in people with dementia. Methods: The literature search included medical peer-reviewed English language publications indexed in Embase, Medline, Cochrane library and Web of Sciences, published up to the 5th of April 2019. Keywords included MESH terms and phrases synonymous with “dementia”, “sensor”, “patient”, “monitoring”, “behavior”, and “therapy”. Studies applying both cross sectional and prospective designs, either as randomized controlled trials, cohort studies, and case-control studies were included. The study was registered in PROSPERO 3rd of May 2019. Results: A total of 1,337 potential publications were identified in the search, of which 34 were included in this review after the systematic exclusion process. Studies were classified according to the type of technology used, as (1) wearable sensors, (2) non-wearable motion sensor technologies, and (3) assistive technologies/smart home technologies. Half of the studies investigated how temporarily dense data on motion can be utilized as a proxy for behavior, indicating high validity of using motion data to monitor behavior such as sleep disturbances, agitation and wandering. Further, up to half of the studies represented proof of concept, acceptability and/or feasibility testing. Overall, the technology was regarded as non-intrusive and well accepted. Conclusions: Targeted clinical application of specific technologies is poised to revolutionize precision care in dementia as these technologies may be used both by patients and caregivers, and at a systems level to provide safe and effective care. To highlight awareness of legal regulations, data risk assessment, and patient and public involvement, we propose a necessary framework for sustainable ethical innovation in healthcare technology. The success of this field will depend on interdisciplinary cooperation and the advance in sustainable ethic innovation.publishedVersio

Social Robots in Hospitals: A Systematic Review

Hospital environments are facing new challenges this century. One of the most important is the quality of services to patients. Social robots are gaining prominence due to the advantages they offer; in particular, several of their main uses have proven beneficial during the pandemic. This study aims to shed light on the current status of the design of social robots and their interaction with patients. To this end, a systematic review was conducted using WoS and MEDLINE, and the results were exhaustive analyzed. The authors found that most of the initiatives and projects serve the el- derly and children, and specifically, that they helped these groups fight diseases such as dementia, autism spectrum disorder (ASD), cancer, and diabetes

Distributed Computing and Monitoring Technologies for Older Patients

This book summarizes various approaches for the automatic detection of health threats to older patients at home living alone. The text begins by briefly describing those who would most benefit from healthcare supervision. The book then summarizes possible scenarios for monitoring an older patient at home, deriving the common functional requirements for monitoring technology. Next, the work identifies the state of the art of technological monitoring approaches that are practically applicable to geriatric patients. A survey is presented on a range of such interdisciplinary fields as smart homes, telemonitoring, ambient intelligence, ambient assisted living, gerontechnology, and aging-in-place technology. The book discusses relevant experimental studies, highlighting the application of sensor fusion, signal processing and machine learning techniques. Finally, the text discusses future challenges, offering a number of suggestions for further research directions