Dataset Information

Detection of Real-World Trips in At-Fall Risk Community Dwelling Older Adults Using Wearable Sensors.

ABSTRACT: Background: Near-falls such as a trip, slip, stumble, or misstep involve a loss of balance (LOB) that does not result in a fall, occur more frequently than actual falls, and are associated with an increased fall risk. To date, studies have largely involved detection of simulated laboratory LOBs using wearable devices in young adults. Data on the detection of and kinematics of naturally occurring LOBs in people at high risk of falling are lacking. This may provide a new way to identify older adults at high risk for falls. We aimed to explore key body kinematics underlying real-world trips in at-fall risk community dwelling older adults wearing inertial measurement units (IMU). Methods: Five community-dwelling older adults with a history of falls who reported trips during the study period participated. They wore a voice recorder and 4 IMUs mounted on feet, lower back and wrist for two consecutive weeks to provide a record of the context and timing of LOB events. Sensor data prior to time-stamped voice recording of a trip were processed in order to visually identify unusual foot trajectories and lower back and arm orientations. Then, data of feet, lower back and wrist position and orientation were combined to create a three-dimensional animation representing the estimated body motion during the noted time segments in order to corroborate the occurrence of a trip. Events reported as a trip by the participant and identified as a trip by a researcher, blinded to voice recordings description, were included in the final analysis. Results: A total of 18 trips obtained from five participants were analyzed. Twelve trips occurred at home, three outside and for three the location was not reported. Trips were identified in the sensor data by observing (1) additional peaks to the typical foot velocity signal during swing phase; (2) increased velocity of the contralateral foot and (3) sharp changes in lower back pitch angles. Conclusions: Our approach demonstrates the feasibility of identifying and studying the mechanisms and context underlying trip-related LOBs in at-fall risk older adults during real world activities.

SUBMITTER: Handelzalts S

PROVIDER: S-EPMC7492551 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Detection of Real-World Trips in At-Fall Risk Community Dwelling Older Adults Using Wearable Sensors.

Handelzalts Shirley S Alexander Neil B NB Mastruserio Nicholas N Nyquist Linda V LV Strasburg Debra M DM Ojeda Lauro V LV

Frontiers in medicine 20200902

<b>Background:</b> Near-falls such as a trip, slip, stumble, or misstep involve a loss of balance (LOB) that does not result in a fall, occur more frequently than actual falls, and are associated with an increased fall risk. To date, studies have largely involved detection of simulated laboratory LOBs using wearable devices in young adults. Data on the detection of and kinematics of naturally occurring LOBs in people at high risk of falling are lacking. This may provide a new way to identify old ...[more]

PMID: 32984385

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Project description:IntroductionFall rates and fall-related injuries among community-dwelling older adults (≥65 years) are expected to increase rapidly, due to the aging population worldwide. Fall prevention programs (FPPs), consisting of strength and balance exercises, have been proven effective in reducing fall rates among older adults. However, these FPPs have not reached their full potential as most programs are under-enrolled. Therefore, this study aims to identify promising strategies that promote participation in FPPs among community-dwelling older adults.MethodsThis is an exploratory qualitative study. Previously, barriers and facilitators for participation in FPPs by older adults had been identified. Next, six strategies had been designed using the Intervention Mapping approach: (1) reframing; (2) informing about benefits; (3) raising awareness of risks; (4) involving social environment; (5) offering tailored intervention; (6) arranging practicalities. Strategies were validated during semi-structured interviews with community-dwelling older adults (n = 12) at risk of falling. Interviews were audio-recorded, transcribed, and analyzed following a qualitative thematic methodology, with a hybrid approach.ResultsAll strategies were considered important by at least some of the respondents. However, two strategies stood out: (1) reframing 'aging' and 'fall prevention': respondents preferred to be approached differently, taking a 'life course' perspective about falls, and avoiding confronting words; and (2) 'informing about benefits' (e.g., 'living independently for longer'); which was mentioned to improve the understanding of the relevance of participating in FPPs. Other strategies were considered important to take into account too, but opinions varied more strongly.DiscussionThis study provides insight into potential strategies to stimulate older adults to participate in FPPs. Results suggest that reframing 'aging' and 'fall prevention' may facilitate the dialogue about fall prevention, by communicating differently about the topic, for example 'staying fit and healthy', while focusing on the benefits of participating in FPPs. Gaining insight into the strategies' effectiveness and working mechanisms is an area for future research. This could lead to practical recommendations and help professionals to enhance older adults' participation in FPPs. Currently, the strategies are further developed to be applied and evaluated for effectiveness in multiple field labs in a central Dutch region (Utrecht).

Project description:BackgroundFalls pose a severe threat to the health of older adults worldwide. Determining gait and kinematic parameters that are related to an increased risk of falls is essential for developing effective intervention and fall prevention strategies. This study aimed to investigate the discriminatory parameter, which lay an important basis for developing effective clinical screening tools for identifying high-fall-risk older adults.MethodsForty-one individuals aged 65 years and above living in the community participated in this study. The older adults were classified as high-fall-risk and low-fall-risk individuals based on their BBS scores. The participants wore an inertial measurement unit (IMU) while conducting the Timed Up and Go (TUG) test. Simultaneously, a depth camera acquired images of the participants' movements during the experiment. After segmenting the data according to subtasks, 142 parameters were extracted from the sensor-based data. A t-test or Mann-Whitney U test was performed on the parameters for distinguishing older adults at high risk of falling. The logistic regression was used to further quantify the role of different parameters in identifying high-fall-risk individuals. Furthermore, we conducted an ablation experiment to explore the complementary information offered by the two sensors.ResultsFifteen participants were defined as high-fall-risk individuals, while twenty-six were defined as low-fall-risk individuals. 17 parameters were tested for significance with p-values less than 0.05. Some of these parameters, such as the usage of walking assistance, maximum angular velocity around the yaw axis during turn-to-sit, and step length, exhibit the greatest discriminatory abilities in identifying high-fall-risk individuals. Additionally, combining features from both devices for fall risk assessment resulted in a higher AUC of 0.882 compared to using each device separately.ConclusionsUtilizing different types of sensors can offer more comprehensive information. Interpreting parameters to physiology provides deeper insights into the identification of high-fall-risk individuals. High-fall-risk individuals typically exhibited a cautious gait, such as larger step width and shorter step length during walking. Besides, we identified some abnormal gait patterns of high-fall-risk individuals compared to low-fall-risk individuals, such as less knee flexion and a tendency to tilt the pelvis forward during turning.

Project description:BACKGROUND:Wearable devices are valuable assessment tools for patient outcomes in contexts such as clinical trials. To be successfully deployed, however, participants must be willing to wear them. Another concern is that usability studies are rarely published, often fail to test devices beyond 24 hours, and need to be repeated frequently to ensure that contemporary devices are assessed. OBJECTIVE:This study aimed to compare multiple wearable sensors in a real-world context to establish their usability within an older adult (>50 years) population. METHODS:Eight older adults wore seven devices for a minimum of 1 week each: Actigraph GT9x, Actibelt, Actiwatch, Biovotion, Hexoskin, Mc10 Biostamp_RC, and Wavelet. Usability was established through mixed methods using semistructured interviews and three questionnaires, namely, the Intrinsic Motivation Inventory (IMI), the System Usability Scale (SUS), and an acceptability questionnaire. Quantitative data were reported descriptively and qualitative data were analyzed using deductive content analysis. Data were then integrated using triangulation. RESULTS:Results demonstrated that no device was considered optimal as all scored below average in the SUS (median, IQR; min-max=57.5, 12.5; 47.5-63.8). Hexoskin was the lowest scored device based on the IMI (3.6; 3.4-4.5), while Biovotion, Actibelt, and Mc10 Biostamp_RC achieved the highest median results on the acceptability questionnaire (3.6 on a 6-point Likert scale). Qualitatively, participants were willing to accept less comfort, less device discretion, and high charging burdens if the devices were perceived as useful, namely through the provision of feedback for the user. Participants agreed that the purpose of use is a key enabler for long-term compliance. These views were particularly noted by those not currently wearing an activity-tracking device. Participants believed that wrist-worn sensors were the most versatile and easy to use, and therefore, the most suitable for long-term use. In particular, Actiwatch and Wavelet stood out for their comfort. The convergence of quantitative and qualitative data was demonstrated in the study. CONCLUSIONS:Based on the results, the following context-specific recommendations can be made: (1) researchers should consider their device selection in relation to both individual and environmental factors, and not simply the primary outcome of the research study; (2) if researchers do not wish their participants to have access to feedback from the devices, then a simple, wrist-worn device that acts as a watch is preferable; (3) if feedback is allowed, then it should be made available to help participants remain engaged; this is likely to apply only to people without cognitive impairments; (4) battery life of 1 week should be considered as a necessary feature to enhance data capture; (5) researchers should consider providing additional information about the purpose of devices to participants to support their continued use.

Dataset Information

Detection of Real-World Trips in At-Fall Risk Community Dwelling Older Adults Using Wearable Sensors.

Publications

Detection of Real-World Trips in At-Fall Risk Community Dwelling Older Adults Using Wearable Sensors.

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