Keywords: Aging in place Elders In-home sensor technology Length of stay RN care coordination Sen... more Keywords: Aging in place Elders In-home sensor technology Length of stay RN care coordination Senior housing a b s t r a c t Background: When planning the Aging in Place Initiative at TigerPlace, it was envisioned that advances in technology research had the potential to enable early intervention in health changes that could assist in proactive management of health for older adults and potentially reduce costs. Purpose: The purpose of this study was to compare length of stay (LOS) of residents living with environmentally embedded sensor systems since the development and implementation of automated health alerts at TigerPlace to LOS of those who are not living with sensor systems. Estimate potential savings of living with sensor systems. Methods: LOS for residents living with and without sensors was measured over a span of 4.8 years since the implementation of sensor-generated health alerts. The group living with sensors (n ¼ 52) had an average LOS of 1,557 days (4.3 years); the comparison group without sensors (n ¼ 81) was 936 days (2.6 years); p ¼ .0006. Groups were comparable based on admission age, gender, number of chronic illnesses, SF12 physical health, SF12 mental health, Geriatric Depression Scale (GDS), activities of daily living, independent activities of daily living, and mini-mental status examination scores. Both groups, all residents living at TigerPlace since the implementation of health alerts, receive registered nurse (RN) care coordination as the standard of care. Discussion: Results indicate that residents living with sensors were able to reside at TigerPlace 1.7 years longer than residents living without sensors, suggesting that proactive use of health alerts facilitates successful aging in place. Health alerts, generated by automated algorithms interpreting environmentally
Background: Higher levels of functional health in older adults leads to higher quality of life an... more Background: Higher levels of functional health in older adults leads to higher quality of life and improves the ability to age-in-place. Tracking functional health objectively could help clinicians to make decisions for interventions in case of health deterioration. Even though several geriatric assessments capture several aspects of functional health, there is limited research in longitudinally tracking personalized functional health of older adults using a combination of these assessments. Methods: We used geriatric assessment data collected from 150 older adults to develop and validate a functional health prediction model based on risks associated with falls, hospitalizations, emergency visits, and death. We used mixed effects logistic regression to construct the model. The geriatric assessments included were Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and Short Form 12 (SF12). Construct validators such as fall risks associated with model predictions, and case studies with functional health trajectories were used to validate the model. Results: The model is shown to separate samples with and without adverse health event outcomes with an area under the receiver operating characteristic curve (AUC) of > 0.85. The model could predict emergency visit or hospitalization with an AUC of 0.72 (95% CI 0.65-0.79), fall with an AUC of 0.86 (95% CI 0.83-0.89), fall with hospitalization with an AUC of 0.89 (95% CI 0.85-0.92), and mortality with an AUC of 0.93 (95% CI 0.88-0.97). Multiple comparisons of means using Turkey HSD test show that model prediction means for samples with no adverse health events versus samples with fall, hospitalization, and death were statistically significant (p < 0.001). Case studies for individual residents using predicted functional health trajectories show that changes in model predictions over time correspond to critical health changes in older adults. Conclusions: The personalized functional health tracking may provide clinicians with a longitudinal view of overall functional health in older adults to help address the early detection of deterioration trends and decide appropriate interventions. It can also help older adults and family members take proactive steps to improve functional health.
This paper describes the iterative process in which voice-assisted technology (VAT) has been inte... more This paper describes the iterative process in which voice-assisted technology (VAT) has been integrated with an in-home sensor system to enable older adults to better manage their health. Through pilot research, a user interface was developed and is currently being deployed in older adults' homes. This ongoing research has the ability to help older adults remain independent in their own homes and can assist informal caregivers in providing at-home supports.
Sensing technologies hold enormous potential for early detection of health changes that can drama... more Sensing technologies hold enormous potential for early detection of health changes that can dramatically affect the aging experience. In previous work, we developed a health alert system that captures and analyzes in-home sensor data. The purpose of this research was to collect input from older adults and family members on how the health information generated can best be adapted, such that older adults and family members can better self-manage their health. Five 90-minute focus groups were conducted with 23 older adults (mean age = 80 years; 87% female) and fi ve family members (mean age = 64; 100% female). Participants were asked open-ended questions about the sensor technology and methods for interacting with their health information. Participants provided feedback regarding tailoring the technology, such as delegating access to family and health care providers, receiving health messages and alerts, interpreting health messages, and graphic display options. Participants also noted concerns and future likelihood of technology adoption. [Journal of Geron-tological Nursing, 46(7), 35-40.]
Journal of the American Medical Directors Association, 2013
Qualitatively describe the use of team and group processes in intervention facilities participati... more Qualitatively describe the use of team and group processes in intervention facilities participating in a study targeted to improve quality of care in nursing homes &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;in need of improvement.&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; A randomized, two-group, repeated-measures design was used to test a 2-year intervention for improving quality of care and resident outcomes. Intervention group (n = 29) received an experimental multilevel intervention designed to help them: (1) use quality improvement methods, (2) use team and group process for direct-care decision-making, (3) focus on accomplishing the basics of care, and (4) maintain more consistent nursing and administrative leadership committed to communication and active participation of staff in decision-making. The qualitative analysis revealed a subgroup of homes (&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Full Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;) likely to continue quality improvement activities that were able to effectively use teams. &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Full Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; had either the nursing home administrator or director of nursing who supported and were actively involved in the quality improvement work of the team. &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Full Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; also selected care topics for the focus of their quality improvement team, instead of &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;communication&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; topics of the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Partial Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; or &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Non-Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; in the study who were identified as unlikely to continue to continue quality improvement activities after the intervention. &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Full Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; had evidence of the key elements of complexity science: information flow, cognitive diversity, and positive relationships among staff; this evidence was lacking in other subgroups. All subgroups were able to recruit interdisciplinary teams, but only those that involved leaders were likely to be effective and sustain team efforts at quality improvement of care delivery systems. Results of this qualitative analysis can help leaders and medical directors use the key elements and promote information flow among staff, residents, and families; be inclusive as discussions about care delivery, making sure diverse points of view are included; and help build positive relationships among all those living and working in the nursing home. Wide-spread adoption of the intervention in the randomized study is feasible and could be enabled by nursing home Medical Directors in collaborative practice with Advanced Practice Nurses.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
We present an approach for patient activity recognition in hospital rooms using depth data collec... more We present an approach for patient activity recognition in hospital rooms using depth data collected using a Kinect sensor. Depth sensors such as the Kinect ensure that activity segmentation is possible during day time as well as night while addressing the privacy concerns of patients. It also provides a technique to remotely monitor patients in a non-intrusive manner. An existing fall detection algorithm is currently generating fall alerts in several rooms in the University of Missouri Hospital (MUH). In this paper we describe a technique to reduce false alerts such as pillows falling off the bed or equipment movement. We do so by detecting the presence of the patient in the bed for the times when the fall alert is generated. We test our algorithm on 96 hours obtained in two hospital rooms from MUH.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2012
Falling is a common health problem for more than a third of the United States population over 65.... more Falling is a common health problem for more than a third of the United States population over 65. We are currently developing a Doppler radar based fall detection system that already has showed promising results. In this paper, we study the sensor positioning in the environment with respect to the subject. We investigate three sensor positions, floor, wall and ceiling of the room, in two experimental configurations. Within each system configuration, subjects performed falls towards or across the radar sensors. We collected 90 falls and 341 non falls for the first configuration and 126 falls and 817 non falls for the second one. Radar signature classification was performed using a SVM classifier. Fall detection performance was evaluated using the area under the ROC curves (AUCs) for each sensor deployment. We found that a fall is more likely to be detected if the subject is falling toward or away from the sensor and a ceiling Doppler radar is more reliable for fall detection than a w...
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012
Falls are a significant cause of injury and accidental death among persons over the age of 65. Ga... more Falls are a significant cause of injury and accidental death among persons over the age of 65. Gait velocity is one of the parameters which have been correlated to the risk of falling. We aim to build a system which monitors gait in seniors and reports any changes to caregivers, who can then perform a clinical assessment and perform corrective and preventative actions to reduce the likelihood of falls. In this paper, we deploy a Doppler radar-based gait measurement system into the apartments of thirteen seniors. In scripted walks, we show the system measures gait velocity with a mean error of 14.5% compared to the time recorded by a clinician. With a calibration factor, the mean error is reduced to 10.5%. The radar is a promising sensing technology for gait velocity in a day-to-day senior living environment.
2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
In this paper, we present results of an automatic vision-based gait assessment tool, using two ca... more In this paper, we present results of an automatic vision-based gait assessment tool, using two cameras. Elderly residents from TigerPlace, a retirement community, were recruited to participate in the validation and test of the system in scripted scenarios representing everyday activities. The residents were first tested on a GAITRite mat, an electronic walkway that captures footfalls, and with inexpensive web cameras recording images. The extracted gait parameters from the camera system were compared with the GAITRite; excellent agreement was achieved. The residents then participated in the scenarios, with only the cameras recording. We found that the residents displayed different gait patterns during the realistic scenarios compared to the GAITRite runs. This finding provides support of the importance and advantage of continuous gait assessment in a daily living environment. Results on 4 elderly participants are included in the paper.
Falling is a common health problem for elders. It is reported that more than one third of seniors... more Falling is a common health problem for elders. It is reported that more than one third of seniors 65 and older fall each year in the United States. We develop a dual Doppler radar system for fall detection. The radar system generates a specific Doppler signature for each human activity which is then categorized by a set of classifiers as fall or non-fall.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
The purpose of this study was to implement a web based application to provide the ability to rewi... more The purpose of this study was to implement a web based application to provide the ability to rewind and review depth videos captured in hospital rooms to investigate the event chains that led to patient's fall at a specific time. In this research, Kinect depth images are being used to capture shadow-like images of the patient and their room to resolve concerns about patients' privacy. As a result of our previous research, a fall detection system has been developed and installed in hospital rooms, and fall alarms are generated if any falls are detected by the system. Then nurses will go through the stored depth videos to investigate for possible injury as well as the reasons and events that may have caused the patient's fall to prevent future occurrences. This paper proposes a novel web application to ease the process of search and reviewing the videos by means of new visualization techniques to highlight video frames that contain potential risk of fall based on our previ...
Passive sensor networks were deployed in independent living apartments to monitor older adults in... more Passive sensor networks were deployed in independent living apartments to monitor older adults in their home environments to detect signs of impending illness and alert clinicians so they can intervene and prevent or delay significant changes in health or functional status. A retrospective qualitative deductive content analysis was undertaken to refine health alerts to improve clinical relevance to clinicians as they use alerts in their normal workflow of routine care delivery to older adults. Clinicians completed written free-text boxes to describe actions taken (or not) as a result of each alert; they also rated the clinical significance (relevance) of each health alert on a scale of 1 to 5. Two samples of the clinician&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s written responses to the health alerts were analyzed after alert algorithms had been adjusted based on results of a pilot study using health alerts to enhance clinical decision-making. In the first sample, a total of 663 comments were generated by seven clinicians in response to 385 unique alerts; there are more comments than alerts because more than one clinician rated the same alert. The second sample had a total of 142 comments produced by three clinicians in response to 88 distinct alerts. The overall clinical relevance of the alerts, as judged by the content of the qualitative comments by clinicians for each alert, improved from 33.3% of the alerts in the first sample classified as clinically relevant to 43.2% in the second. The goal is to produce clinically relevant alerts that clinicians find useful in daily practice. The evaluation methods used are described to assist others as they consider building and iteratively refining health alerts to enhance clinical decision making.
Falls are a major cause of injury in the elderly with almost 1/3 rd of people aged 65 and more fa... more Falls are a major cause of injury in the elderly with almost 1/3 rd of people aged 65 and more falling each year . This work aims to use gait measurements from everyday living environments to estimate risk of falling and enable improved interventions. For this purpose, we consider the use of low-cost pulse-Doppler range control radar. These radars can continuously acquire data during normal activity of a person in night and day conditions and even in the presence of obstructing furniture. A short-time Fourier transform of the radar data reveals unique Doppler signatures from the torso motion and the leg swings. Two algorithms that can extract these features from the radar spectrogram are proposed in this study for estimating gait velocity and stride durations. The performance of the proposed radar system is evaluated with experimental data, which consists of 9 different walk types and a total of 27 separate tests. A high accuracy motion-capture camera system has also been used to acquire data simultaneously with the radar and provides the ground truth reference. Results indicate that the proposed radar system is a viable candidate for gait characterization and can be used to accurately track mean gait velocity, mean stride duration and stride duration variability. The gait velocity variability can also be estimated but with relatively larger error levels.
Proceedings of the 5th International ICST Conference on Pervasive Computing Technologies for Healthcare, 2011
Falling is a common health problem for elderly. It is reported that more than one third of adults... more Falling is a common health problem for elderly. It is reported that more than one third of adults 65 and older fall each year in the United States. To address the problem, we are currently developing a Doppler radar-based fall detection system. Doppler radar sensors provide an inexpensive way to recognize human activity. In this paper, we employed melfrequency cepstral coefficients (MFCC) to represent the Doppler signatures of various human activities such as walking, bending down, falling, etc. Then we used two different classifiers, SVM and kNN, to automatically detect falls based on the extracted MFCC features. We obtained encouraging classification results on a pilot dataset that contained 109 falls and 341 non-fall human activities.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
This paper describes the ongoing work of detecting falls in independent living senior apartments.... more This paper describes the ongoing work of detecting falls in independent living senior apartments. We have developed a fall detection system with Doppler radar sensor and implemented ceiling radar in real senior apartments. However, the detection accuracy on real world data is affected by false alarms inherent in the real living environment, such as motions from visitors. To solve this issue, this paper proposes an improved framework by fusing the Doppler radar sensor result with a motion sensor network. As a result, performance is significantly improved after the data fusion by discarding the false alarms generated by visitors. The improvement of this new method is tested on one week of continuous data from an actual elderly person who frequently falls while living in her senior home.
The purpose of this study was to test the implementation of a fall detection and "rewind" privacy... more The purpose of this study was to test the implementation of a fall detection and "rewind" privacy-protecting technique using the Microsoft ® Kinect ™ to not only detect but prevent falls from occurring in hospitalized patients. Kinect sensors were placed in six hospital rooms in a step-down unit and data were continuously logged. Prior to implementation with patients, three researchers performed a total of 18 falls (walking and then falling down or falling from the bed) and 17 non-fall events (crouching down, stooping down to tie shoe laces, and lying on the floor). All falls and non-falls were correctly identified using automated algorithms to process Kinect sensor data. During the first 8 months of data collection, processing methods were perfected to manage data and provide a "rewind" method to view events that led to falls for post-fall quality improvement process analyses. Preliminary data from this feasibility study show that using the Microsoft Kinect sensors provides detection of falls, fall risks, and facilitates quality improvement after falls in real hospital environments unobtrusively, while taking into account patient privacy. Figure 1. Example of a depth image showing the patient and a visitor in the hospital room.
This study aim is to explore the perceptions of seniors in regard to "smart home" technology aimi... more This study aim is to explore the perceptions of seniors in regard to "smart home" technology aiming to improve their quality of life and/or monitor their health status. A total of 15 older adults participated in three focus groups. Participants had a positive attitude towards these technologies and identified application areas such as emergency help, detection of falls, monitoring of physiological parameters. Concerns were expressed about privacy and the need for tailored training.
Keywords: Aging in place Elders In-home sensor technology Length of stay RN care coordination Sen... more Keywords: Aging in place Elders In-home sensor technology Length of stay RN care coordination Senior housing a b s t r a c t Background: When planning the Aging in Place Initiative at TigerPlace, it was envisioned that advances in technology research had the potential to enable early intervention in health changes that could assist in proactive management of health for older adults and potentially reduce costs. Purpose: The purpose of this study was to compare length of stay (LOS) of residents living with environmentally embedded sensor systems since the development and implementation of automated health alerts at TigerPlace to LOS of those who are not living with sensor systems. Estimate potential savings of living with sensor systems. Methods: LOS for residents living with and without sensors was measured over a span of 4.8 years since the implementation of sensor-generated health alerts. The group living with sensors (n ¼ 52) had an average LOS of 1,557 days (4.3 years); the comparison group without sensors (n ¼ 81) was 936 days (2.6 years); p ¼ .0006. Groups were comparable based on admission age, gender, number of chronic illnesses, SF12 physical health, SF12 mental health, Geriatric Depression Scale (GDS), activities of daily living, independent activities of daily living, and mini-mental status examination scores. Both groups, all residents living at TigerPlace since the implementation of health alerts, receive registered nurse (RN) care coordination as the standard of care. Discussion: Results indicate that residents living with sensors were able to reside at TigerPlace 1.7 years longer than residents living without sensors, suggesting that proactive use of health alerts facilitates successful aging in place. Health alerts, generated by automated algorithms interpreting environmentally
Background: Higher levels of functional health in older adults leads to higher quality of life an... more Background: Higher levels of functional health in older adults leads to higher quality of life and improves the ability to age-in-place. Tracking functional health objectively could help clinicians to make decisions for interventions in case of health deterioration. Even though several geriatric assessments capture several aspects of functional health, there is limited research in longitudinally tracking personalized functional health of older adults using a combination of these assessments. Methods: We used geriatric assessment data collected from 150 older adults to develop and validate a functional health prediction model based on risks associated with falls, hospitalizations, emergency visits, and death. We used mixed effects logistic regression to construct the model. The geriatric assessments included were Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and Short Form 12 (SF12). Construct validators such as fall risks associated with model predictions, and case studies with functional health trajectories were used to validate the model. Results: The model is shown to separate samples with and without adverse health event outcomes with an area under the receiver operating characteristic curve (AUC) of > 0.85. The model could predict emergency visit or hospitalization with an AUC of 0.72 (95% CI 0.65-0.79), fall with an AUC of 0.86 (95% CI 0.83-0.89), fall with hospitalization with an AUC of 0.89 (95% CI 0.85-0.92), and mortality with an AUC of 0.93 (95% CI 0.88-0.97). Multiple comparisons of means using Turkey HSD test show that model prediction means for samples with no adverse health events versus samples with fall, hospitalization, and death were statistically significant (p < 0.001). Case studies for individual residents using predicted functional health trajectories show that changes in model predictions over time correspond to critical health changes in older adults. Conclusions: The personalized functional health tracking may provide clinicians with a longitudinal view of overall functional health in older adults to help address the early detection of deterioration trends and decide appropriate interventions. It can also help older adults and family members take proactive steps to improve functional health.
This paper describes the iterative process in which voice-assisted technology (VAT) has been inte... more This paper describes the iterative process in which voice-assisted technology (VAT) has been integrated with an in-home sensor system to enable older adults to better manage their health. Through pilot research, a user interface was developed and is currently being deployed in older adults' homes. This ongoing research has the ability to help older adults remain independent in their own homes and can assist informal caregivers in providing at-home supports.
Sensing technologies hold enormous potential for early detection of health changes that can drama... more Sensing technologies hold enormous potential for early detection of health changes that can dramatically affect the aging experience. In previous work, we developed a health alert system that captures and analyzes in-home sensor data. The purpose of this research was to collect input from older adults and family members on how the health information generated can best be adapted, such that older adults and family members can better self-manage their health. Five 90-minute focus groups were conducted with 23 older adults (mean age = 80 years; 87% female) and fi ve family members (mean age = 64; 100% female). Participants were asked open-ended questions about the sensor technology and methods for interacting with their health information. Participants provided feedback regarding tailoring the technology, such as delegating access to family and health care providers, receiving health messages and alerts, interpreting health messages, and graphic display options. Participants also noted concerns and future likelihood of technology adoption. [Journal of Geron-tological Nursing, 46(7), 35-40.]
Journal of the American Medical Directors Association, 2013
Qualitatively describe the use of team and group processes in intervention facilities participati... more Qualitatively describe the use of team and group processes in intervention facilities participating in a study targeted to improve quality of care in nursing homes &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;in need of improvement.&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; A randomized, two-group, repeated-measures design was used to test a 2-year intervention for improving quality of care and resident outcomes. Intervention group (n = 29) received an experimental multilevel intervention designed to help them: (1) use quality improvement methods, (2) use team and group process for direct-care decision-making, (3) focus on accomplishing the basics of care, and (4) maintain more consistent nursing and administrative leadership committed to communication and active participation of staff in decision-making. The qualitative analysis revealed a subgroup of homes (&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Full Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;) likely to continue quality improvement activities that were able to effectively use teams. &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Full Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; had either the nursing home administrator or director of nursing who supported and were actively involved in the quality improvement work of the team. &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Full Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; also selected care topics for the focus of their quality improvement team, instead of &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;communication&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; topics of the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Partial Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; or &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Non-Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; in the study who were identified as unlikely to continue to continue quality improvement activities after the intervention. &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Full Adopters&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; had evidence of the key elements of complexity science: information flow, cognitive diversity, and positive relationships among staff; this evidence was lacking in other subgroups. All subgroups were able to recruit interdisciplinary teams, but only those that involved leaders were likely to be effective and sustain team efforts at quality improvement of care delivery systems. Results of this qualitative analysis can help leaders and medical directors use the key elements and promote information flow among staff, residents, and families; be inclusive as discussions about care delivery, making sure diverse points of view are included; and help build positive relationships among all those living and working in the nursing home. Wide-spread adoption of the intervention in the randomized study is feasible and could be enabled by nursing home Medical Directors in collaborative practice with Advanced Practice Nurses.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
We present an approach for patient activity recognition in hospital rooms using depth data collec... more We present an approach for patient activity recognition in hospital rooms using depth data collected using a Kinect sensor. Depth sensors such as the Kinect ensure that activity segmentation is possible during day time as well as night while addressing the privacy concerns of patients. It also provides a technique to remotely monitor patients in a non-intrusive manner. An existing fall detection algorithm is currently generating fall alerts in several rooms in the University of Missouri Hospital (MUH). In this paper we describe a technique to reduce false alerts such as pillows falling off the bed or equipment movement. We do so by detecting the presence of the patient in the bed for the times when the fall alert is generated. We test our algorithm on 96 hours obtained in two hospital rooms from MUH.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2012
Falling is a common health problem for more than a third of the United States population over 65.... more Falling is a common health problem for more than a third of the United States population over 65. We are currently developing a Doppler radar based fall detection system that already has showed promising results. In this paper, we study the sensor positioning in the environment with respect to the subject. We investigate three sensor positions, floor, wall and ceiling of the room, in two experimental configurations. Within each system configuration, subjects performed falls towards or across the radar sensors. We collected 90 falls and 341 non falls for the first configuration and 126 falls and 817 non falls for the second one. Radar signature classification was performed using a SVM classifier. Fall detection performance was evaluated using the area under the ROC curves (AUCs) for each sensor deployment. We found that a fall is more likely to be detected if the subject is falling toward or away from the sensor and a ceiling Doppler radar is more reliable for fall detection than a w...
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012
Falls are a significant cause of injury and accidental death among persons over the age of 65. Ga... more Falls are a significant cause of injury and accidental death among persons over the age of 65. Gait velocity is one of the parameters which have been correlated to the risk of falling. We aim to build a system which monitors gait in seniors and reports any changes to caregivers, who can then perform a clinical assessment and perform corrective and preventative actions to reduce the likelihood of falls. In this paper, we deploy a Doppler radar-based gait measurement system into the apartments of thirteen seniors. In scripted walks, we show the system measures gait velocity with a mean error of 14.5% compared to the time recorded by a clinician. With a calibration factor, the mean error is reduced to 10.5%. The radar is a promising sensing technology for gait velocity in a day-to-day senior living environment.
2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
In this paper, we present results of an automatic vision-based gait assessment tool, using two ca... more In this paper, we present results of an automatic vision-based gait assessment tool, using two cameras. Elderly residents from TigerPlace, a retirement community, were recruited to participate in the validation and test of the system in scripted scenarios representing everyday activities. The residents were first tested on a GAITRite mat, an electronic walkway that captures footfalls, and with inexpensive web cameras recording images. The extracted gait parameters from the camera system were compared with the GAITRite; excellent agreement was achieved. The residents then participated in the scenarios, with only the cameras recording. We found that the residents displayed different gait patterns during the realistic scenarios compared to the GAITRite runs. This finding provides support of the importance and advantage of continuous gait assessment in a daily living environment. Results on 4 elderly participants are included in the paper.
Falling is a common health problem for elders. It is reported that more than one third of seniors... more Falling is a common health problem for elders. It is reported that more than one third of seniors 65 and older fall each year in the United States. We develop a dual Doppler radar system for fall detection. The radar system generates a specific Doppler signature for each human activity which is then categorized by a set of classifiers as fall or non-fall.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
The purpose of this study was to implement a web based application to provide the ability to rewi... more The purpose of this study was to implement a web based application to provide the ability to rewind and review depth videos captured in hospital rooms to investigate the event chains that led to patient's fall at a specific time. In this research, Kinect depth images are being used to capture shadow-like images of the patient and their room to resolve concerns about patients' privacy. As a result of our previous research, a fall detection system has been developed and installed in hospital rooms, and fall alarms are generated if any falls are detected by the system. Then nurses will go through the stored depth videos to investigate for possible injury as well as the reasons and events that may have caused the patient's fall to prevent future occurrences. This paper proposes a novel web application to ease the process of search and reviewing the videos by means of new visualization techniques to highlight video frames that contain potential risk of fall based on our previ...
Passive sensor networks were deployed in independent living apartments to monitor older adults in... more Passive sensor networks were deployed in independent living apartments to monitor older adults in their home environments to detect signs of impending illness and alert clinicians so they can intervene and prevent or delay significant changes in health or functional status. A retrospective qualitative deductive content analysis was undertaken to refine health alerts to improve clinical relevance to clinicians as they use alerts in their normal workflow of routine care delivery to older adults. Clinicians completed written free-text boxes to describe actions taken (or not) as a result of each alert; they also rated the clinical significance (relevance) of each health alert on a scale of 1 to 5. Two samples of the clinician&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s written responses to the health alerts were analyzed after alert algorithms had been adjusted based on results of a pilot study using health alerts to enhance clinical decision-making. In the first sample, a total of 663 comments were generated by seven clinicians in response to 385 unique alerts; there are more comments than alerts because more than one clinician rated the same alert. The second sample had a total of 142 comments produced by three clinicians in response to 88 distinct alerts. The overall clinical relevance of the alerts, as judged by the content of the qualitative comments by clinicians for each alert, improved from 33.3% of the alerts in the first sample classified as clinically relevant to 43.2% in the second. The goal is to produce clinically relevant alerts that clinicians find useful in daily practice. The evaluation methods used are described to assist others as they consider building and iteratively refining health alerts to enhance clinical decision making.
Falls are a major cause of injury in the elderly with almost 1/3 rd of people aged 65 and more fa... more Falls are a major cause of injury in the elderly with almost 1/3 rd of people aged 65 and more falling each year . This work aims to use gait measurements from everyday living environments to estimate risk of falling and enable improved interventions. For this purpose, we consider the use of low-cost pulse-Doppler range control radar. These radars can continuously acquire data during normal activity of a person in night and day conditions and even in the presence of obstructing furniture. A short-time Fourier transform of the radar data reveals unique Doppler signatures from the torso motion and the leg swings. Two algorithms that can extract these features from the radar spectrogram are proposed in this study for estimating gait velocity and stride durations. The performance of the proposed radar system is evaluated with experimental data, which consists of 9 different walk types and a total of 27 separate tests. A high accuracy motion-capture camera system has also been used to acquire data simultaneously with the radar and provides the ground truth reference. Results indicate that the proposed radar system is a viable candidate for gait characterization and can be used to accurately track mean gait velocity, mean stride duration and stride duration variability. The gait velocity variability can also be estimated but with relatively larger error levels.
Proceedings of the 5th International ICST Conference on Pervasive Computing Technologies for Healthcare, 2011
Falling is a common health problem for elderly. It is reported that more than one third of adults... more Falling is a common health problem for elderly. It is reported that more than one third of adults 65 and older fall each year in the United States. To address the problem, we are currently developing a Doppler radar-based fall detection system. Doppler radar sensors provide an inexpensive way to recognize human activity. In this paper, we employed melfrequency cepstral coefficients (MFCC) to represent the Doppler signatures of various human activities such as walking, bending down, falling, etc. Then we used two different classifiers, SVM and kNN, to automatically detect falls based on the extracted MFCC features. We obtained encouraging classification results on a pilot dataset that contained 109 falls and 341 non-fall human activities.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
This paper describes the ongoing work of detecting falls in independent living senior apartments.... more This paper describes the ongoing work of detecting falls in independent living senior apartments. We have developed a fall detection system with Doppler radar sensor and implemented ceiling radar in real senior apartments. However, the detection accuracy on real world data is affected by false alarms inherent in the real living environment, such as motions from visitors. To solve this issue, this paper proposes an improved framework by fusing the Doppler radar sensor result with a motion sensor network. As a result, performance is significantly improved after the data fusion by discarding the false alarms generated by visitors. The improvement of this new method is tested on one week of continuous data from an actual elderly person who frequently falls while living in her senior home.
The purpose of this study was to test the implementation of a fall detection and "rewind" privacy... more The purpose of this study was to test the implementation of a fall detection and "rewind" privacy-protecting technique using the Microsoft ® Kinect ™ to not only detect but prevent falls from occurring in hospitalized patients. Kinect sensors were placed in six hospital rooms in a step-down unit and data were continuously logged. Prior to implementation with patients, three researchers performed a total of 18 falls (walking and then falling down or falling from the bed) and 17 non-fall events (crouching down, stooping down to tie shoe laces, and lying on the floor). All falls and non-falls were correctly identified using automated algorithms to process Kinect sensor data. During the first 8 months of data collection, processing methods were perfected to manage data and provide a "rewind" method to view events that led to falls for post-fall quality improvement process analyses. Preliminary data from this feasibility study show that using the Microsoft Kinect sensors provides detection of falls, fall risks, and facilitates quality improvement after falls in real hospital environments unobtrusively, while taking into account patient privacy. Figure 1. Example of a depth image showing the patient and a visitor in the hospital room.
This study aim is to explore the perceptions of seniors in regard to "smart home" technology aimi... more This study aim is to explore the perceptions of seniors in regard to "smart home" technology aiming to improve their quality of life and/or monitor their health status. A total of 15 older adults participated in three focus groups. Participants had a positive attitude towards these technologies and identified application areas such as emergency help, detection of falls, monitoring of physiological parameters. Concerns were expressed about privacy and the need for tailored training.
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Papers by Marilyn Rantz