Joseph T. Gwin, Ph.D. - US grants

DESCRIPTION (provided by applicant): Strength and balance training has been demonstrated to prevent physical decline and falls in older adults. The majority of fall prevention studies have focused on supervised group or home-based exercise interventions utilizing qualified personal. The implementation of these interventions on a community-wide level is limited due to home-bound status because of functional or cognitive decline, care-giving responsibilities, or transportation difficulties. High costs for personal, and lack of group exercie facilities are likewise problematic. A promising and cost-effective approach for tailoring strength and balance exercise to older adults in a community setting is to provide training via the internet. However, interactive web-based home exercise technologies, including virtually supervised training, have not yet been developed. The objective of this collaborative SHIFT SBIR project between BioSensics LLC (Cambridge, MA) and the University of Arizona (Interdisciplinary Consortium on Advance Motion Performance (iCAMP) and Arizona Center on Aging) is to develop a low cost, easy-to-use, interactive web application for home-based strength and balance training to improve mobility and reduce fall risk in older adults. The proposed system will be developed based on an existing non-interactive prototype web-based training program using a virtual on- screen trainer. The new interactive web application will include an on-screen 'user avatar' that mimics its users movements. This will be accomplished by developing an instrumented overshoe containing kinematic sensors. Based on the sensor signals, body segment kinematics (e.g., foot position, ankle angle, and hip angle) will be estimated in real-time using a simplified biomechanical model of the human body. The kinematic data will drive the on-screen user avatar, which will provide real-time feedback to the user regarding their exercise performance. Game-based features will be included for rewarding correctly performed exercises and motivating the user to achieve individually set exercise goals based on his/her initial motor performance. To ensure user-friendliness, the application will be developed based on established guidelines for media use in older adults. In the first of two clinical studies we will evaluate the accuracy of the estimates of lower extremity kinematics during exercise provided by the new system. In the second clinical study (a randomized controlled trial) we will evaluate the effectiveness of the proposed technology for improving mobility, gait, balance, quality of life, and risk of falling compared to unsupervised home trainin. Several validated outcome measures will be used to assess training-related changes in functional performance, as well as user perceived acceptability/usability of the new technology. A unique element of the present study is that both exercise adherence and exercise accuracy will be objectively assessed. A larger clinical study to further assess the benefits of the proposed technology for improving mobility and reducing falls in older adults is planned for Phase II of this project. In addition, in Phase II additional hardware and software development will be performed to make the system suitable for commercialization to the target population. The proposed technology could have an important effect on the US health care system by reducing the risk of falling and improving function, quality-of-life, and independence among older adults. This methodology addresses key issues for an aging population with high risk of falling and multiple disease processes. Moreover, the methods evaluated and refined in this study will be used in future web-based applications focused on exercise training in various disease processes that effect mobility and balance, such as stroke, diabetes, and dementia.

DESCRIPTION (provided by applicant): The public health problem addressed by this proposal is that inactivity in individuals with chronic disabilities who use a wheelchair results in signifiant and costly secondary complications, such as pressure ulcers, obesity, diabetes, osteoporosis, and cardiovascular comorbidities. We propose an interactive telehealth monitoring and auto-biofeedback system to promote physical activity, pressure relief maneuver performance, and self-management among wheelchair users. In this project we focus on patients with spinal cord injury (SCI) who are at particularly high risk for developing pressure ulcers from sitting too long (31% annual incidence, 85% lifetime incidence). However, the proposed technology is broadly applicable to wheelchair based telehealth. The proposed technology - which attaches to any wheelchair without modification - has three core components: 1) an activity monitoring system (i.e., wheelchair speed, distance travelled, and number of self-propulsions), 2) a pressure relief monitoring system, and 3) a system that provides reminders and feedback regarding the achievement of pressure relief and physical activity goals. Biofeedback will be delivered locally (to the user) via a wheelchair mounted display and remotely (to the clinician) via a secure internet interface. The enabling technologies are innovative sensor systems to monitor wheelchair specific activity patterns but the significant value comes from integrating these novel measurements within biofeedback system that encourages wheelchair users to actively avoid secondary complications of inactivity and allows care providers to identify at risk patients and intervene efficiently. Existing technologies do not compare with the proposed solution. Products exist to monitor wheelchair seat pressure but these products are costly, cumbersome, and not designed for home use. Products exist to monitor wheelchair specific physical activity but these devices cannot distinguish passive from active wheelchair movement. No existing technology combines these measures with auto-biofeedback and telehealth functionality. The team we have assembled for this collaborative project includes engineers, clinicians, and scientists from BioSensics (a privately held biomedical technology development company) and Rancho Los Amigos National Rehabilitation Center (one of the largest comprehensive rehabilitation centers in the United States). In addition, this project benefits from the consultation of a world-renowned expert in physical activity monitoring (Dr. Bijan Najafi, University of Arizona), as well as a leading expert and critical decision maker in SCI care (Dr. Sophia Chun, Chief of SCI, Veterans Health Administration). This team has collaborated successfully on prior projects. The Specific Aims of Phase I are to 1) improve prototyped and pilot tested versions of the proposed system by leveraging existing BioSensics technologies commercialized through prior NIH SBIR awards; 2) validate the measurements of the proposed system using state-of-the-art tools including a high-density pressure mat and camera-based motion capture, and 3) evaluate the efficacy of local biofeedback (to the user via a wheelchair mounted display) during community usage. By demonstrating that biofeedback increases physical activity and achievement of pressure relief will justify further NIH investment in the proposed technology. Within 6 months of the completion of Phase I, we anticipate having a commercially available beta release of the system (BioSensics has successfully brought several products to market in this timeframe). In Phase II we will develop the remote monitoring and telehealth aspects of the proposed system by adding automatic wireless data transfer capabilities (via mobile and Wi-Fi networks) and developing a secure website for remotely accessing activity data and sending telehealth reminders to the wheelchair mounted display.

? DESCRIPTION (provided by applicant): Falls are the leading cause of fatal and nonfatal injuries among older adults (>65 years) and result in $30 billion in annual medical costs. Medical alert devices, commonly worn as a pendant, can be used to signal for help in the event of a fall. More recently, medical alert devices with automatic fall detection functionality have been developed. These devices use accelerometry to detect a fall and can signal for help if the wearer forgets to, or is incapable of, pressing the alert button. Widespread adoption of these devices has been limited by the prevalence of undetected falls and false alerts, and by the lack of publically available studies documenting the sensitivity and false alarm rate of commercially-available fall detection devices under real-world settings. BioSensics, in collaboration with the Interdisciplinary Consortium on Advanced Motion Performance and the Arizona Center on Aging at the University of Arizona, developed a medical alert pendant (ActivePERSTM) with automatic fall detection, activity monitoring, and non-compliance alerts through a Phase I & II STTR from the National Institute on Aging. ActivePERS was developed using data from simulated falls and simulated activities of daily living in a laboratory setting. In this setting, ActivePERS has 100% sensitivity and specificity. However, these fall detection algorithms have not been adequately characterized under real-world conditions. The primary objectives of this proposal are to test ActivePERS in a real-world setting, and to improve the ActivePERS fall detection algorithm to achieve an optimal trade-off between sensitivity and false alarm rate, based on acceleration data from real-world falls. In addition, we intend to extend the use of ActivePERS to the detection of near falls. The detection of near falls could enable novel outcome measures aimed to evaluate the effectiveness of interventions designed to achieve a decrease in falls and near falls in older adults. To accomplish these objectives, 200 community-dwelling older adults will wear a fall detection sensor for a period of 12 months. The sensor will be configured to detect falls based on existing algorithms, as well as to record raw tri-axial accelerometer signals for th purposes of algorithm improvements and development of a novel algorithm to detect near falls. Detected falls and near falls will be compared to self-reported falls and near falls. This ambitiou project would not typically be possible given the budget constraints of a Phase II SBIR. However, the present proposal represents a unique partnership between BioSensics and Partners Healthcare (the largest healthcare provider in New England). Partners Healthcare is a trial site in an ongoing, multi-site, $30 million research grant, funded by the Patient-Centered Outcomes Research Institute (PCORI), to find effective and evidence-based strategies for falls prevention. By leveraging the extensive ongoing patient recruitment and relying on the ongoing study for collection of self-reported fall logs, we will be able to achieve the stated objectives within the SBIR budget constraints. The proposed study will provide the largest dataset to date of real-world falls and uniquely position BioSensics to commercialize a reliable fall detection technology.

? DESCRIPTION (provided by applicant): We propose to further develop, field test, and commercialize a reliable and robust sensor technology that allows the objective assessment of daily physical activity, risk of falling, frailty, and activity organization among older adults in he home and community. This is a Phase IIB STTR application. During Phases I&II BioSensics, LLC, in collaboration with the Interdisciplinary Consortium on Advanced Motion Performance and the Arizona Center on Aging at the University of Arizona, developed and clinically validated sophisticated signal processing algorithms and associated sensor hardware to monitor physical activity and falls in older adults using a single motion sensor (tri-axial accelerometer) worn on the torso or as a pendant. Our Phase I/II work resulted in two commercially available products. PAMSys(tm) is a wearable sensor platform for long-term monitoring of activity related parameters that are of significant importance for objective assessment of physical activity, functioning, frailty, and fall risk of older adults. PAMSys(tm) is primarily a research tool with broad applicatons in pharmaceutical clinical trials and other comparative outcomes clinical research. ActivePERS(tm) is a low-cost medical alert pendant with automatic fall detection, activity monitoring, and non-compliance alerts. ActivePERS(tm) is a consumer product that has been commercialized through 9 on-going partnerships with companies in the telehealth and medical alert markets. With this Phase IIB project we propose to improve our ActivePERS(tm) technology to enable long-term remote monitoring of fall risk and frailty status. An objective method for earl diagnosis, intervention and remote monitoring of the risk of falling/frailty using physical activit telemonitoring and feedback has not yet been developed. Such technology could be used to identify patterns indicative of early changes allowing early diagnosis and intervention of at-risk elders. In addition, it will enable remote and continuous screening of the risk of falling/frailty during daily life, supporting autonomy and quality of life, and limiting the need for clinical intervention. Moreover, the technology can provide an objective tool to evaluate the effects of rehabilitation on motor function, and hence on reductions in the risk of falling/frailty based on te relative efficacy of different interventions. There is a significant commercialization potential fo the proposed technology due to 1) the size of the market, 2) the disruptive nature of our first-to-market technology, and 3) the ongoing national push towards increased efforts towards fall prevention. We will have a market-ready device by the completion of this project with plans for a market launch during Phase III.

? DESCRIPTION (provided by applicant): BioSensics LLC, in collaboration with the Department of Surgery at the University of Arizona, proposes to develop, clinically validate, and commercialize the Upper-Limb Frailty Meter (UFM); a novel wearable technology for quantifying frailty in older trauma patients. It is necessary to quantify frailty in these patients to ensure tat treatment is appropriate, risk-stratified, and compatible with high function and quality of life. Despite increasing evidence that assessing frailty facilitates medical decision-making, a quick and clinically simple frailty assessment tool is not available for use in trauma. The UFM is a system of two low cost wearable sensors worn on the wrist and upper arm. It requires 20 seconds of repeated elbow flexion and extension to identify known frailty features such as slowness, weakness, inflexibility, and exhaustion. The UFM is superior to existing approaches to frailty assessment because it can be used in patients who are unable to walk, and it does not require time consuming questionnaires that are not practical in a busy clinical environment. This application is submitted as a Direct to Phase II because a prototype UFM has already been validated in our target population. Among 117 community-dwelling older adults those identified as frail by the Fried criteria were identified by the UFM with 100% sensitivity and specificity (pr-frail individuals were identified with 87% sensitivity and 82% specificity). Among 30 geriatric trauma patients there was an excellent association between the Rockwood frailty index and UFM parameters (r > 0.81, p < 0.01). To commercialize the UFM we must 1) improve sensor hardware for ease of use and cost reduction, 2) demonstrate accurate diagnoses of frailty in a larger sample of non-mobile geriatric trauma patients, 3) provide further evidence that frailty affects clinical outcomes and, therefore, frailty assessment should regularly be used to guide the treatment of geriatric trauma patients, and 4) demonstrate that the UFM does not disrupt the clinical workflow. These are the objectives of the proposed project. The short-term impact of the project is a commercially available tool for more effective and efficient frailty assessment. The long-term impact of the technology and related clinical research (both proposed and in the future) is the application of frailty assessment to understand physiologic vulnerabilities among older trauma patients to improve the clinical prediction of outcomes and facilitate patient-centered communication and decision-making consistent with patients' values and preferences. There is a significant commercialization potential for the proposed technology due to 1) the size of the market, 2) the disruptive nature of our first-to- market technology, and 3) the ongoing national push towards increased reliance on frailty assessment to help guide treatment planning in geriatrics. We will have a market-ready device by the completion of Phase II with plans for a market launch during Phase III, pending FDA approval.

? DESCRIPTION (provided by applicant): Wrist-worn Sensors for Tele-Rehabilitation of the Hemiparetic Upper-Extremity: Stroke and other causes of central nervous system damage can result in debilitating loss of motor control that is often more pronounced in one limb than the other. Using or attempting to use the affected limb during activities of daily living, despite considerable difficulty, stimulates neuroplasticity and motor function recovery. BioSensics, in partnership with the Motion Analysis Laboratory at Spaulding Rehabilitation Hospital, will develop wrist-worn sensors for motor retraining after stroke. Our simple technology will encourage affected limb use during the performance of activities of daily living, will remind patients to perform daily prescribed motor control exercises in the home environment, and will assess the quality of limb movement during these exercises. We hypothesize that adding long-term monitoring and biofeedback using wrist-worn sensors to traditional therapies will improve motor ability following stroke; particularly in cases where a high dosage of physical and occupational therapy is not feasible due to insurance coverage, lack of transportation, geography, or other limiting factors. The proposed device is the only telehealth system designed to encourage usage of the affected limb during activities of daily living. Many technologies exist to remotely monitor movement using wearable sensors, but none address the specific needs of patients with hemiparesis. Therefore, there is a significant opportunity to develop a first-to-market technology in this space. The team we have assembled for this collaborative project includes engineers, clinicians, and scientists from BioSensics (a privately held biomedical technology development company) and Spaulding Rehabilitation Hospital (the largest provider of rehabilitation medicine in New England). During Phase I of this Fast-Track SBIR project we will develop the wrist-worn sensors and test algorithms for assessing the quality and quantity of upper-limb movement in the home environment based on acceleration measured by these sensors. During Phase II we will develop the telehealth infrastructure for the proposed system, including a home base station that receives daily movement summaries from the wrist-worn sensors and uploads the data via WiFi or LAN to a HIPAA compliant server, and a website that clinicians can use to visualize data and remotely set patient specific exercise regimens and activity goals. We will also conduct a usability study and a clinical study at Spaulding Rehabilitation Hospital. The clinical study will compare rehabilitation outcomes between 30 patients with upper-extremity hemiparesis following stroke who receive standard care and supplemental home-based therapy and 30 patients who receive the same intervention but use the proposed system. There is a significant commercialization potential for the proposed technology due to 1) the size of the market, 2) the disruptive nature of our first-to-market technology, and 3) the ongoing national push for a transition from the current fee- for-service healthcare model to accountable-care-organization standards. We will have a market-ready device by the completion of Phase II with plans for a market launch during Phase III, pending FDA approval.

PROJECT SUMMARY/ABSTRACT The skeleton is the third most common site of metastatic cancer, and nearly half of all cancers metastasize to bone. As a result of new and aggressive treatments cancer patients are living longer, but at sites of skeletal metastasis fractures occur in 17%-35% of affected bones after minimal trauma. This significantly impacts patient functioning and quality of life. While much has been learned about the mechanisms of skeletal metastasis, clinicians continue to make subjective assessments regarding a patient's fracture risk. We have developed a method, called Computed Tomography-based Rigidity Analysis (CTRA), to use computed tomography (CT) images to calculate the minimal rigidity of a bone containing a neoplastic lesion for the purposes of estimating load capacity and predicting pathologic fractures. The CTRA method has been validated in ex-vivo, pre-clinical, and in-vivo studies. An alpha version of CTRA was developed for research purposes. While it is not intended or marketed for clinical use, it is being used clinically in several different hospitals at the discretion of a medical doctor. Physicians using CTRA have been inconsistently reimbursed by public and private payers under CPT code 76499 ?Unlisted Diagnostic Radiographic Procedure.? This generic code is used when no other specific procedure code exists. At low volumes during initial deployment this is feasible, but for CTRA to become a standard of care, FDA 510(k) clearance and a non-generic Category I CPT code are needed. Through an ongoing Direct Phase II SBIR we are developing a commercial quality CTRA software package that will integrate with hospital picture archiving and communication systems (PACS) and fully automate the CTRA process. This CRP grant will help us bridge the gap between product development and successful medical software commercialization. Therefore, the first two aims fall into the category of Technical Assistance, whereas the last two aims fall into the Late Stage R&D categories follows: Aim 1: prepare all required documentation for an FDA 510(k) submission for CTRA software: Aim 2: prepare an application to the American Medical Association (AMA) for a Category I CPT code: Aim 3: software design verification and validation activities: and Aim 4: eliminate the need for an imaging phantom. Given the clinical need and proven accuracy of the approach, the Musculoskeletal Tumor Society (MSTS) supports the commercialization of CTRA and has already committed to assisting us in the process of applying for a CPT code (see MSTS Letter of Support).

PROJECT ABSTRACT / SUMMARY Inactivity in individuals with chronic disabilities who use a wheelchair results in significant and costly secondary complications, such as pressure ulcers, obesity, diabetes, osteoporosis, and cardiovascular comorbidities. We propose to develop an interactive telehealth monitoring and biofeedback system to promote physical activity and pressure relief maneuver performance among wheelchair users. In this project we focus on patients with spinal cord injury (SCI) who are at particularly high risk for developing pressure ulcers from sitting too long (31% annual incidence, 85% lifetime incidence). However, the proposed technology is broadly applicable to wheelchair-based telehealth. The proposed technology - which attaches to any wheelchair without modification - has three core components: 1) an activity monitoring system (i.e., detection of wheel-pushes), 2) a pressure relief monitoring system, and 3) reminders and feedback regarding the achievement of pressure relief and physical activity goals. Biofeedback will be delivered locally (to the user) via a smartphone app and remotely (to the clinician) via a secure internet interface. The enabling technologies are innovative sensor systems to monitor wheelchair specific activity patterns but the significant value comes from integrating these novel measurements within a biofeedback system that encourages wheelchair users to actively avoid secondary complications of inactivity and allows care providers to identify at risk patients and intervene efficiently. Existing technologies do not compare with the proposed solution. Products exist to monitor wheelchair seat pressure but these products are costly, cumbersome, and not designed for home use. Products exist to monitor wheelchair specific physical activity but these devices cannot distinguish passive from active wheelchair movement. No existing technology combines these measures with biofeedback and telehealth functionality. The team we have assembled for this collaborative project includes engineers, clinicians, and scientists from BioSensics (a privately held biomedical technology development company) and Rancho Los Amigos National Rehabilitation Center (one of the largest comprehensive rehabilitation centers in the United States). During Phase I of this project we developed and validated a prototype version of wheelchair sensor and smartphone app (Dowling et. al., Wireless Health, 2015; Dowling et. al., Assistive Technologies, In Press). During Phase II we will improve the seat sensor hardware and develop the remote monitoring and telehealth aspects of the proposed system including 1) a secure HIPAA compliant website so patients, caregivers, and clinicians can remotely view activity and pressure relief data, 2) an automated method for pushing alerts to clinicians and caregivers (via SMS or e-mail) if pressure relief or activity goals are not met, and 3) a simple interface so clinicians and caregivers can send telehealth reminders to the wheelchair user?s smartphone app.

PROJECT SUMMARY / ABSTRACT The Focused Assessment with Sonography in Trauma (FAST) exam is the standard of care for rapid detection of abdominal free fluid in emergency medicine and trauma critical care. It is a point-of-care ultrasound exam that incorporates four views of the abdomen. In trauma, abdominal free fluid is assumed to be blood until proven otherwise. Timely detection is critical because if untreated abdominal hemorrhage can rapidly lead to hemorrhagic shock and death. In community hospitals, the FAST exam is underutilized due to limited access to physicians who are able to perform the exam (typically an emergency physician or trauma surgeon). In addition, the low cost and portability of ultrasound make it an ideal triage tool for prehospital settings including extreme environments like mass-casualty and combat zones. In these settings, detection of abdominal free fluid would impact medical transport prioritization and aid in the distribution of limited resources. BioSensics, in collaboration with Boston University School of Medicine, proposes to develop a portable ultrasound system to enable a minimally trained operator to perform and accurately interpret a FAST exam. The system will guide the operator through the image acquisition process and automatically compute a probability for abdominal free fluid. We have previously shown that image processing algorithms can detect free fluid with 100% sensitivity and 90% specificity in perihepatic (e.g., right upper quadrant) abdominal ultrasound views (J. Ultrasound in Medicine, In Press). In this Phase I SBIR project we will improve our image processing algorithms and validate them on FAST exams recorded using a portable ultrasound system. We will also develop a beta version of the system for usability testing and further clinical evaluation in Phase II. By the completion of Phase I the system will be able to concurrently record, and display in realtime, ultrasound images and ultrasound probe position and kinematics. Recording probe position and movement is important because it will assist the software in guiding a minimally trained operator through the image acquisition process. In Phase II we will develop operator guidance software and perform a randomized clinical trial to evaluate efficacy from the perspective of usability (can a minimally trained operator record a diagnostic quality exam) and performance (how much free fluid has to be present for the developed system to reliably detect it). The proposed technology has significant commercialization potential. Our first target market is emergency medical services including civilian ambulance companies and the U.S. military. Important use cases in this market include medical transport prioritization in mass-casualty and combat settings, as well as pre-hospital free-fluid assessment, particularly during longer transports. Our second target market is emergency departments with a focus on rural and community hospitals. Broader applications include use in resource limited global health medicine, as well as in many other specialties where non-trauma assessment of abdominal free fluid is necessary, such as the medically critically ill or to assess for ascites.

ABSTRACT The principal means of measuring motor impairment in Huntington disease (HD) is the Unified Huntington's Disease Rating Scale (UHDRS) total motor score, which is subjective and categorical. Wearable sensors could enable objective, sensitive, continuous assessment of motor impairments in individuals with a variety of neurological movement disorders. This is important because large amounts of objective data acquired at a high frequency in a real-world setting could reduce the time and cost of early stage clinical trials. Clinically, wearable sensors for motor assessment during activities of daily living could be used to expedite and improve medication titration. In HD, wearable sensors that could detect subtle motor abnormalities in the premanifest phase of the disease would be valuable for monitoring early therapeutic intervention trials and could provide insight into the phase of clinical disease onset. We have recently completed a series of pilot studies (1 published article and 1 manuscript in preparation) supported by Auspex Pharmaceuticals (now part of Teva Pharmaceuticals) demonstrating that a wearable sensor on the torso can detect gait related motor impairments in HD and a wearable sensor on the wrist can identify the occurrence and severity of upper extremity chorea. In this Direct to Phase II SBIR we propose to build upon this Phase I equivalent pilot work by developing a telehealth system for continuous remote assessment of Huntington's chorea using wearable sensors. Based on our pilot research we propose to develop a system consisting of two wearables sensors to be worn on the dominant wrist and on the torso. In partnership with the University of Rochester, we will conduct a clinical study to improve and further validate algorithms for detecting chorea severity, and to evaluate whether sensor-derived measures can detect pharmacological response to anti-chorea medication or subtle motor abnormalities in the premanifest stage of HD. Participants will visit the clinic at baseline and then once a quarter for a total of 5 visits. Assessments will include the motor portion of the UHDRS, Q-motor assessment, a Timed-Up-and-Go walking test, and a series of simulated activities of daily living. This assessment will be conducted twice, on- and off-medication. Participants will wear the two sensors during in-clinic assessments and for a period of 1-week thereafter. There is a significant commercialization potential for the proposed technology. This includes pharmaceutical clinical trials, where the promise of wearable sensors has led to significant investment in the development of technologies for Parkinson's disease. However, the smaller patient population of individuals with Huntington's disease has been completely overlooked. This represents both a significant public health need and market opportunity for BioSensics. Teva Pharmaceuticals, who provided the financial support for our Phase I equivalent pilot work, and the Huntington's Disease Society of America have expressed an interest in the proposed technology and are supportive of our efforts (see Letters of Support).

ABSTRACT With a Phase I/II STTR grant award from NIA, BioSensics in collaboration with Baylor College of Medicine (BCM) successfully developed and commercialized an advanced physical activity monitoring system (PAMSys?) for older adults. PAMSys enables continuous remote monitoring of physical activity, fall risk, and fall incidents. The fall detection technology of PAMSys has become the gold standard in the medical alert industry through multiple licensing agreements. To date, more than 100,000 medical alert devices with BioSensics technology have been sold by our licensing partners. However, PAMSys is not capable of monitoring Instrumental Activities of Daily Living (IADL) such as cooking, shopping, and managing medication. Monitoring IADL is essential for timely diagnosis of dementia, monitoring disease progression, and determining when additional care services are needed. In one of our pilot clinical studies using PAMSys, we identified specific activity patterns (e.g., transitions between different postures, short walking bouts) in individuals with cognitive impairment who were monitored during activities of daily living. In addition, BioSensics has developed an initial prototype of a smart wireless device, called CliQ, that enables interactions with objects at home, while also simplifying the user interaction with smart home devices and smartphone apps. Armed with this technical expertise and pilot clinical data, we propose to design and commercialize a platform for continuous monitoring of IADL. This innovative solution, called IADLSys?, is based on the following three technologies that will work collectively to provide crucial insight into deterioration in cognitive status and trajectory toward loss of independence: 1) wireless tags that are attached to various objects of interest in the user?s living environment, 2) a wearable sensor that measures physical activity, as well as proximity to the wireless tags, and 3) software that unobtrusively monitors the usage of applications associated with daily functioning and social engagement to provide a picture of the user?s virtual IADL to complement the monitoring of their physical IADL (usage time only, no private application data is monitored). IADLSys also includes a hub to transfer all data to a secure backend server that will be used for data storage and processing. In Phase I, we will design an initial version of IADLSys and examine the feasibility of the proposed platform for identifying IADL of interest, including using a telephone, preparing a meal, doing laundry, taking medication, vacuuming, and others in the target population. In Phase II, we will complete the development of IADLSys including implementation of live uploading protocols and the cloud-computing backend to host collected data. A robust data-security architecture will be implemented to protect patient?s privacy. In addition, we will carry out a clinical study to evaluate if the data gathered and analyzed by IADLSys can discriminate those with Mild Neurocognitive Disorder (previously termed Mild Cognitive Impairment), and Major Neurocognitive Disorder due to Alzheimer?s Disease (AD) with mild severity, from cognitively intact aged matched healthy individuals.

ABSTRACT Falls are a major cause of morbidity and mortality in dementia. The first step in any fall prevention program is to identify patients at risk. Unfortunately, existing methods for fall risk screening are not adequate for patients with dementia. In a recent pilot study, we demonstrated that conventional fall risk assessment methods are not able to predict prospective falls in people with dementia. However, in the same study, we demonstrated that physical activity (PA) parameters are independent predictors of fall risk in persons with dementia. An advantage of assessing fall risk using PA-based parameters is that this can be done remotely and continuously, which is critical for early intervention. Through our prior STTR awards, we have developed and commercialized a wearable platform to automatically detect falls and remotely monitor day-to-day fluctuations in risk of falling in older adults without dementia. In our currently funded NIH CRP project we aim to further improve this system by, among other things, adapting it for a wrist-worn form factor. With this supplementary funding, we plan to expand our efforts under the CRP project to include the development of a PA-based fall risk assessment method specifically for patients with dementia. This is significant because PA-based fall risk algorithms for patients without dementia should not be used for patients with dementia because their daily activities are different. Furthermore, we have shown that the PA- parameters that are predictive of falls in community dwelling older adults are not the same as the PA-parameters that are predictive of falls in dementia. Therefore, it is necessary to develop a unique fall risk assessment algorithm for the dementia population. In the project supplement, we propose to expand the clinical study to include patient with dementia. We will recruit a cohort of 70 people with confirmed dementia (age 75+) and enroll them in a shortened clinical study of 6 months duration (compared to 1 year for the CRP project). Based on these data, and records of confirmed falls during the study period, we will develop a PA-based fall risk assessment algorithm specific for patients with dementia. We will also collect conventional assessments including performance-based tests (Timed-up-and-go, Performance-Oriented-Mobility-Assessment, 5-chair-stand), and questionnaires (cognition, ADL-status, fear of falling, depression, history of falls) for comparison. Finally, as a part of this project supplement we will integrate the newly developed fall risk algorithm into commercially available medical alert devices, based on our currently established partnerships.