Technology for Prevention and Reduction of Disease and Disability

Chronic conditions, including cardiovascular diseases, diabetes or physical injuries due to falls and other accidents have significant costs for people, the healthcare system and the Canadian economy. However, close monitoring of chronic conditions can significantly reduce their effects. In addition, regular activity and exercise in older adults is associated with an overall improvement in health, functional capacity, quality of life and independence. Research in TECH-DD is producing technologies and tools that will help to actively engage older adults in society. We are developing novel ambient-based and on-person technologies that can measure physiological and activity data; systems that can mitigate the risk of injury from accidents, such as falls; and new technological platforms for exercise and prevention of injury and disability. These technologies will be transferred to market through our industry partners. Results will also inform new approaches to improve care practices and reduce healthcare expenditures.

Workpackage Leads
  • Rafik Goubran, Carleton University
  • Frank Knoefel,


Core Research Projects

Ambient-Based Physiological and Functional Monitoring – 5.1 AMBI-MON

Effective monitoring of at-risk older adults, whether in the home or in hospital, can help increase their safety, prevent hospitalization and promptly alert health-care providers when an intervention is needed. This project focuses on the development of sensor systems that can be embedded in the person’s environment and that deliver health and functional information in real time. For example, a bed-based pressure sensor will collect information on breathing, bed movements and characteristics of getting out of bed—all helpful in monitoring respiratory health, risk of skin breakdown and transfer safety. The goal is to quickly detect any changes in health and ability so that early interventions can prevent further decline and enhance safety.

Project Leads
  • Rafik Goubran, Carleton University
  • Frank Knoefel,
Researchers
  • Andreas Ejupi, Simon Fraser University
  • Bruce Wallace, Carleton University
  • Hilmi Dajani, University of Ottawa
  • James Green, Carleton University
  • Jean Chouinard, Elisabeth Bruyere Hospital
  • Martin Bouchard, University of Ottawa
  • Neil Thomas, Bruyere Research Institute
  • Sarah Fraser, University of Ottawa

 

Technologies to Predict, Prevent, and Detect Falls – 5.2 PRED-FALL

Falls are the largest cause of injuries in adults over age 65. The aim of this project is to develop and evaluate new technologies to predict, detect and prevent falls and fall-related injuries among people at high risk in both long-term care and acute care environments. To learn more about predicting falls, we are analyzing real-life data, acquired both through networks of video cameras in long-term care facilities and with wearable sensors. Our goal is to identify differences in movement patterns during falls. In the area of fall prevention, the team is developing and evaluating low-cost solutions such as compliant flooring, fall mats and padded furniture along with wearable protective gear.

Technologies to predict, prevent and detect falls

Project Leads
  • Fabio Feldman, Fraser Health
  • Steve Robinovitch, Simon Fraser University
Researchers
  • Alex Mihailidis, Toronto Rehab Institute, University Health Network
  • Alexandra Korall, University of Manitoba
  • Andreas Ejupi, Simon Fraser University
  • Carolyn Sparrey, Simon Fraser University
  • Chantelle Lachance, St. Michael's Hospital
  • Dawn Mackey, Simon Fraser University
  • Ed Park, Simon Fraser University
  • Emily O'Hearn, Simon Fraser University
  • Greg Mori, Simon Fraser University
  • Jane Devji, Delta View Enrichment Centre
  • Karim Khan, Centre for Hip Health and Mobility
  • Leslie Karmazinuk, New Vista Society
  • Ming Leung, New Vista Society
  • Omar Aziz, Simon Fraser University
  • Ryan D'Arcy, Simon Fraser University
  • Salim Devji, Delta View Enrichment Centre
  • Samudra Dissanayake, Innovation Boulevard
  • Yijian Yang, University of British Columbia

 

An In-home Intelligent Exercise System for Physical Rehabilitation, Enhancing Musculoskeletal Function, and Preventing Adverse Events – 5.3 IIES-PHYS

Having easy and frequent access to supervised and well-planned therapy for sensory and motor functions can help ensure the long-term health of older adults. This team is developing technologies that can be used for delivering appropriate, individualized rehabilitation and exercise programs. Two separate approaches are proposed: one that provides frequent, less intense regimes for in-home use, and the other that provides less frequent but more intense regimes for use under the guidance of a therapist in a rehabilitation or community centre setting. Project co-investigators include Deirdre Dawson, Baycrest/University of Toronto; Nicole Anderson, Baycrest/University of Toronto; Catherine Donnelly, Queen’s University; Kelly Murphy, Baycrest/University of Toronto; and Feng Xie, McMaster University.

Project Leads
  • Mandar Jog, University of Western Ontario
  • Rajni Patel, University of Western Ontario
Researchers
  • Christian Duval, Quebec University
  • James Frank, University of Waterloo
  • Robert Teasell, University of Western Ontario

 

Commercialization of a haptic robot for rehabilitation of the upper limb post-stroke – 5.10-SIP A2

Age is the primary risk factor for stroke. Stroke, a main cause of long-term disability worldwide, can result in weakness and loss of movement control on one side of the body. About 65% of stroke survivors cannot use their affected arm in daily activities. Recovery of mobility and function requires intense, repetitive, and task-specific therapy. Present demands and budget restrictions in healthcare limit necessary intensive individual therapy. Robot-assisted therapy can address this problem by making rehabilitation service provision more effective and efficient by allowing therapists to work with more patients and patients to do therapy without constant therapist supervision. Our team at University of Toronto/Toronto Rehab and Quanser Consulting Inc. have developed a low-cost portable robotic system that is used with on-screen games. We have conducted preliminary usability, feasibility, and effectiveness studies with chronic stroke survivors with moderate arm recovery. Stroke survivors were motivated and reported high therapy satisfaction. Results are promising with respect to mobility gains. Our goal is to commercialize the robotic system by launching a start-up company. To expedite commercialization, the proposed project will develop commercial quality software including 1) upgrades based on our findings to the system’s user interface to make it easier for stroke survivors and therapists to use, and 2) additional therapeutic games to enhance therapy engagement. The availability and clinical use of robotic systems can result in substantial benefits to stroke survivors, therapists, and healthcare services. For stroke survivors, enhanced opportunities for efficient and effective therapy can result in greater motor and functional recovery. Therapists will advance their practice by having additional effective and efficient tools with which to work with patients and with less focus on the repetitive elements of therapy, can offer greater opportunities to work on daily activity and community re-integration goals.

Project Leads
  • Rosalie Wang, University of Toronto
Researchers
  • Debbie Hebert, Toronto Rehab Institute, University Health Network

 

Commercialization of SlingSerter for Home Care – 5.12-SIP A2

Home caregivers’ most challenging activities when caring for individuals with very limited mobility relate to transfers to and from beds, and to mobility-in-bed. Mechanical lifts reduce the demands of these activities, but do not eliminate them. Most notably, for a lift to be used, a sling must first be placed under the care recipient. This is a physically strenuous process if the care recipient cannot assist: either the individual is manually rolled onto one side, then the other to permit sling placement, or a slide sheet is used to pull a sling under their body. Sling placement is particularly difficult for home caregivers who work alone or care for people in low and/or wide beds. Unfortunately, this difficulty is so great that it often reduces the frequency of transfers or leads to the sling being left under the person, thus increasing the risk of pressure ulcers.

SlingSerter is an effortless alternative: sling straps are inflated using compressed air and gently unfurl under the care recipient. Once 3-5 straps have been placed, they are connected to a lift and used to raise the person a short distance above the bed. It is then easy for the caregiver to place a sling, change bedsheets, provide incontinence care, or reposition the person in bed.

This project will make SlingSerter available to home caregivers through a partnership with Prism Medical (a Handicare company), who have an established line of home lifting products. Guided by feedback from homecare providers, family caregivers and care recipients, we will work to prepare a version of SlingSerter that is optimized for homecare. An effortless sling insertion method will reduce physical demands on caregivers, promoting care recipient health and mobility by enabling more frequent transfers and reducing the incentive to leave slings under people between transfers.

Project Leads
  • Jack Callaghan, University of Waterloo
  • Geoff Fernie, Toronto Rehab Institute/University of Toronto

 

Development strategy for an interactive health monitoring system to increase senior independence and well-being – 5.13-SIP A3

This project will build on the previous SIP WP5.7 project completed by Welbi with AGE-WELL. The purpose for this project is to develop improvements for Welbi, a senior care technology company that is helping improve assistive care of older adults (65 years and older) in Canada. The project will focus on the development of a new chatbot feature for Welbi’s mobile health tech application. There are very few senior-focused health applications on the market today that collect detailed quantitative data as well as qualitative data. Welbi will collect quantitative data via its integration with existing wearable technology devices from manufacturers such as Fitbit. This project will help with the development of the new chatbot feature which is powered by machine learning and artificial intelligence, and this will help Welbi collect the qualitative data needed to take its predictive software to the next level.

This project will help Welbi develop a plan and hire the necessary staff to commercialize this new feature of the software platform. AGE-WELL’s portfolio of senior care technologies will benefit from this project. This project will help improve Welbi’s software so that it can have tremendous benefits and major impacts on the lives of seniors living in Canada as well as family members acting as caregivers for them. Welbi’s mobile application has the potential to greatly increase the independence of seniors and ensure they and their family members stay aware of any health changes or potential risks that are detected. The new chatbot will be specifically designed for seniors, and this feature will greatly increase levels of interaction with them. The chatbot will collect data about the senior’s health and well-being, and will also provide health information, related tips, and activity recommendations based on health status, activity levels, location, and weather.

Project Leads
  • Jeff Jutai, University of Ottawa

 

Longitudinal study of bed entry/exit and sleep patterns for older adults through Data Analytics – 5.14-SIP A3

Problem statement
As people age, a number of things change in their lives, including mobility and sleep patterns. Typically, with increasing age mobility declines and fall risk increases. Any acute illness can also affect mobility. Similarly, sleep is increasingly interrupted, such as going to the bathroom more frequently. Poor sleep can cause poor mobility the next day. With the development of sensors that can be deployed in older adults’ homes, there is an opportunity to identify mobility and sleep biomarkers that can predict changes in health status for increased fall risk. However, monitoring potentially thousands of aging older adults is a huge challenge and the IBM Data Analytics tools may provide a platform to be able to meet this challenge.

Research purpose
The SAM3 research team has between 9 and 12 months of continuous bed pressure and corresponding health data and fall history for each of over 20 older community-dwelling adults from a previous project. This big data set provides a unique opportunity to analyze typical longitudinal data as expected in a real deployment within IBM software tools to allow existing lab only implementations to potentially have commercial deployment.

Anticipated impacts
If the research team can convert mat big data into sleep and mobility knowledge that can be used to identify changes in health status, SAM3 will be one step closer to bringing a novel solution to market. Then mats with smart algorithms may be able to identify health changes in older Canadians before they get so severe that they require expensive hospitalizations. A goal will be the identification of methods to implement and scale the analysis algorithms, which is necessary for any sensor based solution to get to market. This would be a win for older Canadians and society as a whole.

Project Leads
  • Bruce Wallace, Carleton University

 

Towards a personalized treatment of overactive bladder – 5.15-SIP A3

Overactive bladder (OAB) is an incurable urinary disorder that affects up to 18% of Canadian adults. Successful treatment can improve quality of life by alleviating anxiety, social withdrawal, depression, and preventing falls while urgently seeking the bathroom. Falls are the largest cause of injuries in adults over age 65, among which OAB is highly prevalent (30%). Current treatment options (and limitations) include: (a) pharmaceuticals (poor patient compliance/side effects); (b) spinal nerve stimulation (expensive and invasive implantable device); and (c) tibial nerve stimulation therapy provided near the ankle (which requires ongoing clinic-based treatment). The clinical efficacy and long-term compliance of these therapies are notably limited. Additionally there can be significant side-effects. We recently showed clinically that our novel saphenous nerve (SAFN) stimulation therapy effectively improved OAB symptoms, without any reported side-effects. We also showed that this could be done using transcutaneous stimulation via stimulation pads applied to the skin rather than requiring a percutaneous needle procedure in the clinic. The goal of this renewal application is to investigate the time course and dose-related treatment profile of our novel OAB therapy in newly-recruited patients. The successful completion of this project will provide an informed approach to treatment titration (i.e. optimizing stimulation regimen) of individual patients using a therapy that can be provided at the patient’s home.
Project Leads
  • Sasha John, University of Toronto
  • Paul Yoo, University of Toronto

 

Wearable sensor-based automatic frailty and fall risk assessment in older adults – 5.16-CAT

Project Leads
  • Ed Park, Simon Fraser University
Researchers
  • Fabio Feldman, Fraser Health
  • Steve Robinovitch, Simon Fraser University

 

Proof of concept development of an active insole to reduce falls in older adults – 5.17-CAT

Project Leads
  • Carolyn Sparrey, Simon Fraser University

 

Rehabilitation as a health strategy for persons with chronic conditions and associated issues of aging: A web based application – 5.18-CAT

Project Leads
  • Julie Richardson, McMaster University
Researchers
  • David Chan, McMaster University
  • Jordan Miller, Queen's University

 

Rehabilitation mobile app for older adults following total knee replacement – 5.19-SIP A4

The average inpatient cost for joint replacement surgery in Canada is more than $1 billion annually (Canadian Institute for Health Information, 2018). It is critical therefore to reduce negative outcomes, such as the need for revision surgeries, through rehabilitation. Currently, 80% of older adults with total knee replacement (TKR) surgery fail to do necessary rehabilitation, resulting in higher rates of revision surgeries and surgical complications, a lower quality of life, higher pain medication use, and considerable cost to the individual and the health-care system. We are proposing a mobile application (app) that can be used at home to motivate and instruct older adults during their recovery following a TKR. The app would provide daily video guided exercises typically prescribed by a physiotherapist, daily reminders such as taking medication, and checklists for identifying early signs of infection after surgery. We have already developed the unique ability to allow an older adult to measure their knee movements (range of motion) with just their mobile device. This is a form of measurement that previously could not have been done without a health-care provider. All of this information: the range of motion, the amount of exercises completed, and the checklist items, are all carefully tracked daily, weekly and monthly and provided to the older adult via the app to track progress. This app tackles key barriers to rehabilitation compliance namely: cost, accessibility and convenience. We will provide a mobile application that is affordable, accessible to the older adult without having to travel for appointments and allows the older adult to complete their rehabilitation in the comfort of their own home.
Project Leads
  • Jonathan Rose, University of Toronto

 

Development of an automatic braking system for rollator walkers – 5.20-SIP A4

Every day, millions of people rely on a rollator walker for support with independent mobility. A key feature of rollator walkers is the ability to lock the brakes in place for stability when standing or sitting (on the device). Current rollator walkers have a manual braking system that requires users to remember to engage the brake to prevent the device from rolling away and causing a fall. This dependence on memory to engage the brake creates a significant safety hazard for users, particularly for those with cognitive impairments (e.g. dementia). This project aims to reduce the risk of falling due to failing to manually engage the brakes on a rollator walker by developing an automatic braking system. The purpose of our research is to develop an automated braking system that is user-friendly and feasible for commercialization. Our method will include user and product testing that trials the device on a population with consideration of parameters such as diagnosis, physical status and cognitive ability. Automatic rollator walker brakes are currently not active in the market, despite millions of rollator walkers used daily. “A simple fall can set in motion a whole cascade of events that is detrimental to seniors and also to the health-care system” (LeClerc, 2017). Most rollator walker users are seniors. An estimated 1/3 of seniors fall at least once annually, with annual spending to treat falls among seniors estimated at $2 billion in Canada and $50 billion in the United States. Preventing falls eliminates injuries, hospitalizations, deconditioning due to prolonged recovery times, chronic pain, and deaths. Our device will facilitate a higher quality of life by facilitating user independence and safety, which promotes ongoing successful aging and improved general fitness. This can save millions of health-care dollars due to fall prevention and maintenance of overall health.
Project Leads
  • James Tung, University of Waterloo

 

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