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

Cost-effectiveness analysis of the digital fall preventive intervention Safe Step among community-dwelling older people aged 70 and older

Falls are the most common cause of injury in older people, with consequences for the individual and society. With an increasing population of older people, falls and related costs are expected to increase. It is crucial to identify scalable and cost-effective interventions and subsequently reduce fall-related costs. The aim was to evaluate the cost-effectiveness of the Safe Step digital fall preventive exercise intervention over a period of 12 years and, in addition, to evaluate the impact of increased recruitment cost and decreased intervention effect. The intervention was evaluated in an observational study in a municipality context targeting community-dwelling older people of age 70 + . A Markov model with five states was used to model the cost-effectiveness of the Safe Step intervention and evaluate quality-adjusted life years (QALYs) and fall-related costs from a societal perspective. By using data from a meta-analysis as basis for the estimated intervention effect, the Safe Step intervention was compared with a no-intervention alternative. The results showed that the Safe Step intervention dominated no intervention. In the sensitivity analysis with the most conservative estimate of intervention effect, the ICER was €7 616 per QALY gained. Hence, Safe Step showed to be a cost-saving fall preventive intervention in older people at risk of falling and potentially cost-effective even with a low estimated intervention effect. Future studies on efficacy of fall preventive digital interventions will contribute in precising effect estimates and enhance the validity of these cost-effectiveness results.

Exploring the feasibility of using a bedside device to help prevent nighttime falls

BACKGROUND

Older people living in the community are at risk of preventable nighttime falls. Technology can support falls interventions but there is a lack of research into this area. A new bedside device called Bide senses movement and changes in light levels and plays a prerecorded message encouraging the user to follow falls prevention advice when trying to mobilise at night.

AIM

To test the feasibility of using the Bide device in a community health service.

METHOD

Healthcare workers were trained in the use of the Bide device and asked to identify potential participants. The research team subsequently recruited participants, provided them with a device and explained how to use it. After four weeks, participants took part in face-to-face semi-structured interviews regarding the acceptability of the device. Participants' fear of falling was calculated before and after the intervention using the Falls Efficacy Scale-International.

FINDINGS

The Bide device appeared to increase patients' confidence to mobilise at night and no adverse events were reported from its use. The device was generally found to be acceptable and easy to use, although one participant found it irritating. Healthcare workers flagged up very few potential participants to the research team, which may have been due to workload pressures and a disconnect between healthcare workers and technology.

CONCLUSION

It appears feasible to study the use of the Bide device for nighttime falls prevention in the community. To enhance recruitment, a member of the research team may be embedded in the clinical team with the aim of proactively identifying potential participants.

Nursing Interventions to Empower Family Caregivers to Manage the Risk of Falling in Older Adults: A Scoping Review

Falls pose a significant risk to older adults, resulting in injuries and declining quality of life. The psychological impact, particularly the fear of falling, impairs their well-being. This pervasive fear affects daily activities, leading to self-imposed limitations and reduced engagement. This review aimed to identify nursing interventions to empower family caregivers to manage the risk of falling in older adults. A scoping review was developed following the JBI framework. We searched the CINAHL, MEDLINE, Nursing & Allied Health Collection, Cochrane Central Register of Controlled Trials, MedicLatina, and Cochrane Database of Systematic Reviews. The findings of this review revealed that out of 460 initially identified records, nine articles met the eligibility criteria and were retained for further in-depth analysis. These articles provided insights into nine distinct categories of nurse interventions: Therapeutic Relationships, Family Involvement, Personalized Care, Health Education, Multifactorial Falls Risk Assessment, Home Modifications, Referral, Transition Between Healthcare Services, and Health Care Consultants. The findings of this review have significant implications for clinical practice, particularly in emphasizing the crucial role of nurses in empowering family caregivers and older adults to manage the risk of falling at home. Healthcare professionals, policymakers, and researchers can benefit from this informative resource to develop strategies and guidelines.

The Role of Digital Technologies in Facilitating Psychosocial Resilience to Sudden Social Isolation Among Older Adults: Lessons Learned from the COVID-19 Pandemic

This study investigated how older adults adopted new technologies in response to sudden social isolation caused by the COVID-19 pandemic and how this adoption was related to their long-term psychosocial well-being. The study involved a 6-month longitudinal survey of 151 older adults and two phone-based focus groups, which informed a semi-structured interview guide and purposive sampling of diverse community-dwelling older adults. We then conducted twenty qualitative interviews and thematic analysis and mapped themes to 6-month quantitative trajectories of psychosocial health. Three themes emerged: first, most participants adopted multiple technologies to maintain social connection and psychosocial well-being. Second, participants felt left behind by certain technologies due to complicated systems or ageist societal norms. Third, pandemic-related community resources promoted technology independence among isolated older adults and those wanting to avoid "burdening" family. Results challenge ageist stereotypes and provide a framework for encouraging access and comfort with multiple technologies to adapt to sudden health crises or disruptive events.

Recurrent Neural Network Methods for Extracting Dynamic Balance Variables during Gait from a Single Inertial Measurement Unit

Monitoring dynamic balance during gait is critical for fall prevention in the elderly. The current study aimed to develop recurrent neural network models for extracting balance variables from a single inertial measurement unit (IMU) placed on the sacrum during walking. Thirteen healthy young and thirteen healthy older adults wore the IMU during walking and the ground truth of the inclination angles (IA) of the center of pressure to the center of mass vector and their rates of changes (RCIA) were measured simultaneously. The IA, RCIA, and IMU data were used to train four models (uni-LSTM, bi-LSTM, uni-GRU, and bi-GRU), with 10% of the data reserved to evaluate the model errors in terms of the root-mean-squared errors (RMSEs) and percentage relative RMSEs (rRMSEs). Independent t-tests were used for between-group comparisons. The sensitivity, specificity, and Pearson's r for the effect sizes between the model-predicted data and experimental ground truth were also obtained. The bi-GRU with the weighted MSE model was found to have the highest prediction accuracy, computational efficiency, and the best ability in identifying statistical between-group differences when compared with the ground truth, which would be the best choice for the prolonged real-life monitoring of gait balance for fall risk management in the elderly.

Clinical Static Balance Assessment: A Narrative Review of Traditional and IMU-Based Posturography in Older Adults and Individuals with Incomplete Spinal Cord Injury

Maintaining a stable upright posture is essential for performing activities of daily living, and impaired standing balance may impact an individual's quality of life. Therefore, accurate and sensitive methods for assessing static balance are crucial for identifying balance impairments, understanding the underlying mechanisms of the balance deficiencies, and developing targeted interventions to improve standing balance and prevent falls. This review paper first explores the methods to quantify standing balance. Then, it reviews traditional posturography and recent advancements in using wearable inertial measurement units (IMUs) to assess static balance in two populations: older adults and those with incomplete spinal cord injury (iSCI). The inclusion of these two groups is supported by their large representation among individuals with balance impairments. Also, each group exhibits distinct aspects in balance assessment due to diverse underlying causes associated with aging and neurological impairment. Given the high vulnerability of both demographics to balance impairments and falls, the significance of targeted interventions to improve standing balance and mitigate fall risk becomes apparent. Overall, this review highlights the importance of static balance assessment and the potential of emerging methods and technologies to improve our understanding of postural control in different populations.

Older Adult Falls in Emergency Medicine, 2023 Update

Of 4 older adults, 1 will fall each year in the United States. Based on 2020 data from the Centers of Disease Control, about 36 million older adults fall each year, resulting in 32,000 deaths. Emergency departments see about 3 million older adults for fall-related injuries with falls having the ability to cause serious injury such as catastrophic head injuries and hip fractures. One-third of older fall patients discharged from the ED experience one of these outcomes at 3 months.

Optimizing a Technology-Based Body and Mind Intervention to Prevent Falls and Reduce Health Disparities in Low-Income Populations: Protocol for a Clustered Randomized Controlled Trial

BACKGROUND

The lack of health care coverage, low education, low motivation, and inconvenience remain barriers to participating in fall prevention programs, especially among low-income older adults. Low-income status also contributes to negative aging self-perceptions and is associated with a high perceived barrier to care. Existing fall prevention intervention technologies do not enable participants and practitioners to interact and collaborate, even with technologies that bring viable strategies to maintain independence, prevent disability, and increase access to quality care. Research is also limited on the use of technology to enhance motivation and help individuals align their perception with physiological fall risk. We developed a novel, 8-week Physio-Feedback Exercise Program (PEER), which includes (1) technology-based physio-feedback using a real-time portable innovative technology-the BTrackS Balance Tracking System, which is reliable and affordable, allows for home testing, and provides feedback and tracks balance progression; (2) cognitive reframing using the fall risk appraisal matrix; and (3) peer-led exercises focusing on balance, strength training, and incorporating exercises into daily activities.

OBJECTIVE

This study consists of 3 aims. Aim 1 is to examine the effects of the technology-based PEER intervention on fall risk, dynamic balance, and accelerometer-based physical activity (PA). Aim 2 is to examine the effects of the PEER intervention on fall risk appraisal shifting and negative self-perceptions of aging. Aim 3 is to explore participants' experiences with the PEER intervention and potential barriers to accessing and adopting the technology-based PEER intervention to inform future research.

METHODS

This is an intention-to-treat, single-blinded, parallel, 2-arm clustered randomized controlled trial study. We will collect data from 340 low-income older adults at baseline (T1) and measure outcomes after program completion (T2) and follow-up at 3 months (T3) and 6 months (T4). Participants will be enrolled if they meet all the following inclusion criteria: aged ≥60 years, cognitively intact, and able to stand without assistance. Exclusion criteria were as follows: a medical condition precluding exercise or PA, currently receiving treatment from a rehabilitation facility, plan to move within 1 year, hospitalized >3 times in the past 12 months, and does not speak English or Spanish.

RESULTS

As of August 2023, the enrollment of participants is ongoing.

CONCLUSIONS

This study addresses the public health problem by optimizing a customized, technology-driven approach that can operate in low-resource environments with unlimited users to prevent falls and reduce health disparities in low-income older adults. The PEER is a novel intervention that combines concepts of physio-feedback, cognitive reframing, and peer-led exercise by motivating a shift in self-estimation of fall risk to align with physiological fall risk to improve balance, PA, and negative aging self-perception.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05778604; https://www.clinicaltrials.gov/ct2/show/study/NCT05778604.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/51899.

Comparison of four machine learning algorithms for a pre-impact fall detection system

In recent years, real-time health monitoring using wearable sensors has been an active area of research. This paper presents an efficient and low-cost fall detection system based on a pair of shoes equipped with inertial sensors and plantar pressure sensors. In addition, four machine learning algorithms (KNN, SVM, RF, and BP neural network) are compared in terms of their detection performance and suitability for pre-impact fall detection. The results show that KNN and BP neural network outperformed the other two algorithms, where KNN had 98.8% sensitivity, 99.8% specificity, and 99.7% accuracy, and BP neural network had 100% sensitivity, 99.8% specificity, and 99.9% accuracy. KNN outperformed BP neural network in terms of fitting ability, and their lead times were both 460.95 ms. The system can provide sufficient intervention time for the wearer in the pre-impact phase and together with the touchdown fall protection device can effectively prevent fall injuries.

Breaking Down Barriers: Findings from a Literature Review on Housing for People with Disabilities in Latin America

Accessibility to housing is crucial for people with disabilities as it provides them with equal opportunities and allows them to live independently. A systematic literature review has been conducted to understand the current research on accessibility in housing for people with disabilities in Latin America. The study analysed 56 papers and used co-word analysis to identify common themes and topics within the documents. The results of the analysis showed that Brazil (61%) is the country with the most research on the subject, physical disability, at 36%, is the impairment most analysed, and interventions or analysis for the older people (45%) in their homes is the most researched type of population. The co-word analysis revealed that topics such as policy, regulations, the use of technologies, ergonomics interventions, and architectural criteria or barriers to the daily life of disabled people were frequently discussed in the papers. Although this work shows a substantial and growing increase in research on housing for people with disabilities in Latin America, it also demonstrates the importance of increasing research on other types of impairment, such as visual and cognitive-intellectual disabilities, and including children, caregivers, or even young adults.

Evaluation of a novel technology-supported fall prevention intervention - study protocol of a multi-centre randomised controlled trial in older adults at increased risk of falls

BACKGROUND

Increasing number of falls and fall-related injuries in an aging society give rise to the need for effective fall prevention and rehabilitation strategies. Besides traditional exercise approaches, new technologies show promising options for fall prevention in older adults. As a new technology-based approach, the hunova robot can support fall prevention in older adults. The objective of this study is to implement and evaluate a novel technology-supported fall prevention intervention using the hunova robot compared to an inactive control group. The presented protocol aims at introducing a two-armed, multi-centre (four sites) randomised controlled trial, evaluating the effects of this new approach on the number of falls and number of fallers as primary outcomes.

METHODS

The full clinical trial incorporates community-dwelling older adults at risk of falls with a minimum age of 65 years. Including a one-year follow-up measurement, all participants are tested four times. The training programme for the intervention group comprises 24-32 weeks in which training sessions are scheduled mostly twice a week; the first 24 training sessions use the hunova robot, these are followed by a home-based programme of 24 training sessions. Fall-related risk factors as secondary endpoints are measured using the hunova robot. For this purpose, the hunova robot measures the participants' performance in several dimensions. The test outcomes are input for the calculation of an overall score which indicates the fall risk. The hunova-based measurements are accompanied by the timed-up-and-go test as a standard test within fall prevention studies.

DISCUSSION

This study is expected to lead to new insights which may help establish a new approach to fall prevention training for older adults at risk of falls. First positive results on risk factors can be expected after the first 24 training sessions using the hunova robot. As primary outcomes, the number of falls and fallers within the study (including the one-year follow-up period) are the most relevant parameters that should be positively influenced by our new approach to fall prevention. After the study completion, approaches to examine the cost-effectiveness and develop an implementation plan are relevant aspects for further steps.

TRIAL REGISTRATION

German Clinical Trial Register (DRKS), ID: DRKS00025897. Prospectively registered 16 August 2021, https://drks.de/search/de/trial/DRKS00025897 .

Clinical Sensor-Based Fall Risk Assessment at an Orthopedic Clinic: A Case Study of the Staff's Views on Utility and Effectiveness

In-hospital falls are a serious threat to patient security and fall risk assessment (FRA) is important to identify high-risk patients. Although sensor-based FRA (SFRA) can provide objective FRA, its clinical use is very limited and research to identify meaningful SFRA methods is required. This study aimed to investigate whether examples of SFRA methods might be relevant for FRA at an orthopedic clinic. Situations where SFRA might assist FRA were identified in a focus group interview with clinical staff. Thereafter, SFRA methods were identified in a literature review of SFRA methods developed for older adults. These were screened for potential relevance in the previously identified situations. Ten SFRA methods were considered potentially relevant in the identified FRA situations. The ten SFRA methods were presented to staff at the orthopedic clinic, and they provided their views on the SFRA methods by filling out a questionnaire. Clinical staff saw that several SFRA tasks could be clinically relevant and feasible, but also identified time constraints as a major barrier for clinical use of SFRA. The study indicates that SFRA methods developed for community-dwelling older adults may be relevant also for hospital inpatients and that effectiveness and efficiency are important for clinical use of SFRA.

Application of Feedforward and Recurrent Neural Networks for Fusion of Data from Radar and Depth Sensors Applied for Healthcare-Oriented Characterisation of Persons' Gait

In this paper, the useability of feedforward and recurrent neural networks for fusion of data from impulse-radar sensors and depth sensors, in the context of healthcare-oriented monitoring of elderly persons, is investigated. Two methods of data fusion are considered, viz., one based on a multilayer perceptron and one based on a nonlinear autoregressive network with exogenous inputs. These two methods are compared with a reference method with respect to their capacity for decreasing the uncertainty of estimation of a monitored person's position and uncertainty of estimation of several parameters enabling medical personnel to make useful inferences on the health condition of that person, viz., the number of turns made during walking, the travelled distance, and the mean walking speed. Both artificial neural networks were trained on the synthetic data. The numerical experiments show the superiority of the method based on a nonlinear autoregressive network with exogenous inputs. This may be explained by the fact that for this type of network, the prediction of the person's position at each time instant is based on the position of that person at the previous time instants.

Can Smart Home Technologies Help Older Adults Manage Their Chronic Condition? A Systematic Literature Review

The management of chronic diseases requires personalized healthcare that allows older adults to manage their diseases at home. This systematic review aimed to describe the smart home technologies used in the management of chronic diseases in older people. A systematic literature review was conducted on four databases and was reported following the PRISMA statement. Nineteen articles were included. The intervention technologies were classified into three groups: smart home, characterized by environmental sensors detecting motion, contact, light, temperature, and humidity; external memory aids, characterized by a partnership between mobile apps and smart home-based activity learning; and hybrid technology, with the integration of multiple technologies, such as devices installed at patients' homes and telemedicine. The health outcomes evaluated are vital signs, medication management, ADL-IADL, mobility, falls, and quality of life. Smart homes show great potential in the management of chronic diseases by favouring the control of exacerbations and increasing patients' safety by providing support in disease management, including support for cognitively impaired older people. The use of smart homes in the community could bring numerous benefits in terms of continuity of care, allowing the constant monitoring of older people by local and hospital health services.

Assessment of a wearable fall prevention system at a veterans health administration hospital

Objective

In-hospital falls are a significant cause of morbidity and mortality. The Veterans Health Administration (VHA) has designated fall prevention as a major focus area. The objective of this report is to assess the performance of a new sensor-enabled wearable system to prevent patient falls.

Methods

An integrated sensor-enabled wearable SmartSock system was utilized to prevent falls at the acute care wards of a large VA hospital. Individual patients were only provided the SmartSocks when they were determined to be at high risk of falling. All fall count rates, with and without using the SmartSock, were evaluated and compared for individual patients. SmartSock sensor and electronic health record data were combined to assess the system's performance from February 10, 2021, through October 31, 2021.

Results

There were 20.7 falls per 1000 ward days of care (WDOC) for those not using the SmartSocks compared to 9.2 falls per 1000 WDOC for patients using the SmartSocks. This represents a reduction of falls by more than half. These findings are further confirmed with a negative binomial regression model, which showed the use of the SmartSock had a statistically significant effect on the rate of falls (p = 0.03) when length of stay was held constant and demonstrated the odds of fall incident rate of 0.48 (95% CI, 0.24-0.92), that is less than half compared to when patients were not wearing the SmartSock.

Conclusion

The use of a sensor-enabled wearable SmartSock fall prevention system resulted in a clinically meaningful and statistically significant decrease in falls in the acute care setting.

"It's Not Just a Plaster Cast, My Leg Is in It!": Patient Experiences: A Qualitative Study

Plaster casts have been used in the treatment of fractures since 1850, and they play an important role in the healing of extremity injuries and operative repairs. Despite the high incidence of fractures and the widespread use of plaster casts in patients with fractures, the quality of counseling in patients with plaster casts has been neglected. There are few studies on the quality of this patient advisement and the nonmedical experiences of patients with plaster casts. We believe that understanding the feelings, thoughts, and experiences of patients who have had plaster casts will contribute to holistic patient care and will guide the planning of such care. The aim of this study was to describe some of the nonmedical experiences of being in a plaster cast and to illustrate these difficulties through patient quotes. This qualitative research study used a qualitative, descriptive approach guided by phenomenology to explore and describe the subjective experiences of patients with plaster casts. Participants consisted of 10 patients with lower extremity fractures, all of whom had been in a plaster cast for at least 6 weeks. Data were collected through in-depth individual interviews using semistructured questionnaires. The content analysis method was used to analyze the data. COREQ (Consolidated Criteria for Reporting Qualitative Research) was used in structuring and reporting the study. Six themes that described the experiences of patients with a plaster cast were determined in the study. These themes were the basic physiological and functional concern, self-image challenges, social roles, dependence/independence, emotions, and the experience of being in a plaster cast. We determined that many aspects of the lives of patients had been affected by being in a plaster cast and that they had experienced not only physiological issues but also psychological, social, emotional, and aesthetic issues. In addition, all the participants stated that they sought solutions to these issues by requesting support from a person or persons around them. Understanding the experiences of individuals with a plaster cast will contribute to the holistic healthcare of individuals who suffer fractures, allowing it to be more patient-centered. This understanding will also support the planning and implementation of patient-centered counseling and education.

Dynamic performance-exposure algorithm for falling risk assessment and prevention of falls in community-dwelling older adults

This study aimed to design a dynamic performance-exposure algorithm for falling risk assessment and prevention of falls in community-dwelling older adults. It involved a cross-sectional and follow-up survey assessing retrospective and prospective falls and respective performance-related, exposure and performance-exposure risk factors. In total, 500 Portuguese community-dwelling adults participated. Data modelling showed significant (p<0.05) relationships between the above risk factors and selected nine key ordered outcomes explaining falls to include in the algorithm: previous falls; health conditions; balance; lower strength; perceiving action boundaries; fat mass; environmental hazards; rest periods; and physical activity. Respective high-, moderate- and low-risk cutoffs were established. The results demonstrated a dynamic relationship between older adults' performance capacity and the exposure to fall opportunity, counterbalanced by the action boundary perception, supporting the build algorithm's conceptual framework. Fall prevention measures should consider the factors contributing most to the individual risk of falling and their distance from low-risk safe values.

Non-Contact Smart Sensing of Physical Activities during Quarantine Period Using SDR Technology

The global pandemic of the coronavirus disease (COVID-19) is dramatically changing the lives of humans and results in limitation of activities, especially physical activities, which lead to various health issues such as cardiovascular, diabetes, and gout. Physical activities are often viewed as a double-edged sword. On the one hand, it offers enormous health benefits; on the other hand, it can cause irreparable damage to health. Falls during physical activities are a significant cause of fatal and non-fatal injuries. Therefore, continuous monitoring of physical activities is crucial during the quarantine period to detect falls. Even though wearable sensors can detect and recognize human physical activities, in a pandemic crisis, it is not a realistic approach. Smart sensing with the support of smartphones and other wireless devices in a non-contact manner is a promising solution for continuously monitoring physical activities and assisting patients suffering from serious health issues. In this research, a non-contact smart sensing through the walls (TTW) platform is developed to monitor human physical activities during the quarantine period using software-defined radio (SDR) technology. The developed platform is intelligent, flexible, portable, and has multi-functional capabilities. The received orthogonal frequency division multiplexing (OFDM) signals with fine-grained 64-subcarriers wireless channel state information (WCSI) are exploited for classifying different activities by applying machine learning algorithms. The fall activity is classified separately from standing, walking, running, and bending with an accuracy of 99.7% by using a fine tree algorithm. This preliminary smart sensing opens new research directions to detect COVID-19 symptoms and monitor non-communicable and communicable diseases.

Instrumented Functional Test for Objective Outcome Evaluation of Balance Rehabilitation in Elderly Fallers: A Clinical Study

<b><i>Introduction:</i></b> Observational tests, e.g., the Berg Balance Scale (BBS) are widely used for balance evaluation in the elderly fallers. However, they do not allow objective outcome evaluation of rehabilitative interventions. This study aimed to investigate, in a clinical setting, the use of inertial measurement units (IMUs) integrated into the BBS test for objective outcome evaluation of balance rehabilitation in elderly fallers compared to conventional BBS scores. <b><i>Methods:</i></b> Thirty-six elderly fallers were recruited from the in-patient population of a geriatrics Clinic. Participants performed the BBS test while wearing 3 IMUs placed on the sternum, sacrum, and tibia of the dominant leg following admission to the clinic. Subsequently, they completed a rehabilitation program for 2–4 weeks. They performed a similar test before their discharge. The physical therapist recorded the BBS scores at both sessions, and the sensor data of the 2-min quiet standing task (BBS task 2) were extracted for objective balance evaluation. Moreover, eleven young adults were recruited to perform a 2-min quiet standing test while wearing the same IMUs. Center-of-pressure (COP) and segmental center-of-mass (COM) accelerations were calculated to estimate time-domain, frequency-domain, and intersegment coordination biomarkers of balance. <b><i>Results:</i></b> COP time- and frequency-domain measures, COM acceleration time-domain measures, and intersegment coordination measures could identify age-related changes in balance of seniors compared to young adults (<i>p</i> &#x3c; 0.05). Moreover, balance biomarkers of senior adults exhibited a reduced sway acceleration and jerkiness in the medial-lateral direction post-rehabilitation (<i>p</i> &#x3c; 0.05). Although the total BBS scores increased post-rehabilitation, sway displacement and velocity did not significantly improve. We observed a significant association between pelvis-leg coordination at high sway oscillations and the total BBS scores pre- and post-rehabilitation. <b><i>Conclusion:</i></b> IMUs enable not only the characterization of underlying causes of impaired balance but also the identification of improved and yet impaired aspects of balance post-rehabilitation. Hence, IMUs allow us to characterize risk factors post-rehabilitation in elderly fallers, whereas the BBS scores only show changes in overall balance. It is crucial to objectively evaluate the effectiveness of such interventions to reduce future falls and their adverse consequences. Therefore, instrumented balance assessment is recommended since it can provide quantitative and objective measures for clinical outcome evaluations.

Recruitment strategies and reach of a digital fall-prevention intervention for community-dwelling older adults

Background

To have an impact on the population's health, preventive interventions have to reach a large proportion of the intended population. Digital solutions show potential for providing wider access to fall preventive exercise. However, there is a lack of knowledge about how to reach the target group. The aim of this study was to describe the recruitment process used in the Safe Step randomised controlled trial and the characteristics of the participants reached.

Methods

Several recruitment methods, both digital and non-digital, were adopted to reach the intended sample size. Sociodemographic parameters from the baseline questionnaire were used to describe participant characteristics. The characteristics were also compared to a representative sample of older adults in the Swedish population.

Results

In total, 1628 older adults were recruited. Social media proved to be the most successful recruitment strategy, through which 76% of the participants were recruited. The participants reached had a mean age of 75.9 years, lived in both urban and rural locations, were already frequent users of the Internet and applications (smartphone/tablet) (79.9%), had higher education (71.9%), and a large proportion were women (79.4%). In comparison with the general population participants in the Safe Step study were more highly educated (p < 0.001), women in the study more frequently lived alone (p < 0.001) and men more often reported poorer self-rated health (p = 0.04). Within the study, men reported a faster deteriorating balance (p = 0.003) and more prescribed medication (p < 0.001) than women.

Conclusion

Recruitment via social media is a useful strategy for reaching older adults, especially women and frequent users of the Internet, for a fully self-managed and digital fall prevention exercise intervention. This study underlines that a range of interventions must be available to attract and suit older adults with different functional statuses and digital skills.

Impact of the abandonment of assistive technologies for mobility on the incidence of serious falls in older adults living at home: Results of the ECOCAT study

Purpose

To examine the impact of discontinuing the use of assistive technology for mobility (ATM) devices on the 6-months incidence of falls in older adults (OA) living at home.

Materials and methods

A medico-socioeconomic survey was performed to collect information on the quality of life and well-being of older adults, before and 6 months after being loaned an ATM device. Personal data (medical, social, and economic) were collected via a geriatric survey.

Results

In all, 102 OA participated in the study. Over the 6-months observation period, 17 (n = 81) serious falls were recorded among participants who were using their ATM device optimally; in those who discontinued device use, 12 falls (n = 21) were recorded (57.1%; p = 0.001). Factors significantly associated with falls at home were living in an urban area (odds ratio [OR]: 11.46; 95% confidence interval [CI]: 1.48; 88.98; p = 0.020), an Instrumental Activities of Daily Living Scale score > 4 (OR: 34.04; 95% CI: 1.59; 727.86; p = 0.024), and discontinuation of ATM device use (OR: 17.41; 95% CI: 2.59; 117.02; p = 0.003).

Conclusion

Discontinuation of ATM device use was associated with an increased risk for serious falls.

Systematic review and meta-analysis of clinical trials: In-hospital use of sensors for prevention of falls

BACKGROUND

Intra-hospital falls have become an important public health problem globally. The use of movement sensors with alarms has been studied as elements with predictive capacity for falls at hospital level. However, in spite of their use in some hospitals throughout the world, evidence is lacking about their effectiveness in reducing intra-hospital falls. Therefore, this study aims to develop a systematic review and meta-analysis of existing scientific literature exploring the impact of using sensors for fall prevention in hospitalized adults and the elderly population.

METHODS

We explored literature based on clinical trials in Spanish, English, and Portuguese, assessing the impact of devices used for hospital fall prevention in adult and elderly populations. The search included databases such as IEEE Xplore, the Cochrane Library, Scopus, PubMed, MEDLINE, and Science Direct databases. The critical appraisal was performed independently by two researchers. Methodological quality was assessed based on the ratings of individual biases. We performed the sum of the results, generating an estimation of the grouped effect (Relative Risk, 95% CI) for the outcome first fall for each patient. We assessed heterogeneity and publication bias. The study followed PRISMA guidelines.

RESULTS

Results were assessed in three randomized controlled clinical trials, including 29,691 patients. A total of 351 (3%) patients fell among 11,769 patients assigned to the intervention group, compared with 426 (2.4%) patients who fell among 17,922 patients assigned to the control group (general estimation RR 1.20, 95% CI 1.04, 1.37, P = .02, I2 = 0%; Moderate GRADE).

CONCLUSION

Our results show an increase of 19% in falls among elderly patients who are users of sensors located in their bed, bed-chair, or chair among their hospitalizations. Other types of sensors such as wearable sensors can be explored as coadjutants for fall prevention care in hospitals.

State-of-the-Art Wearable Sensors and Possibilities for Radar in Fall Prevention

Radar technology is constantly evolving, and new applications are arising, particularly for the millimeter wave bands. A novel application for radar is gait monitoring for fall prevention, which may play a key role in maintaining the quality of life of people as they age. Alarming statistics indicate that one in three adults aged 65 years or older will experience a fall every year. A review of the sensors used for gait analysis and their applications to technology-based fall prevention interventions was conducted, focusing on wearable devices and radar technology. Knowledge gaps were identified, such as wearable radar development, application specific signal processing and the use of machine learning algorithms for classification and risk assessment. Fall prevention through gait monitoring in the natural environment presents significant opportunities for further research. Wearable radar could be useful for measuring gait parameters and performing fall risk-assessment using statistical methods, and could also be used to monitor obstacles in real-time.

User-centered requirements engineering to manage the fuzzy front-end of open innovation in e-health: A study on support systems for seniors' physical activity

BACKGROUND

Although e-health potentials for improving health systems in their safety, quality and efficiency has been acknowledged, a large gap between the postulated and empirically demonstrated benefits of e-health technologies has been ascertained. E-health development has classically been technology-driven, often resulting in the design of devices and applications that ignore the complexity of the real-world setting, thus leading to slow diffusion of innovations to care. Therefore, e-health innovation needs to consider the mentioned complexity already from the start. The early phases of innovation, fuzzy front-end (FFE) defined as "the period between when an opportunity is first considered and when an idea is judged ready for development" has been identified to have the highest impact on the innovation process and its outcome. The FFE has been recognized as the most difficult stage to manage in the innovation process as it involves a high degree of uncertainty. Such a phase becomes even more difficult when different sectors and organizations are involved. Therefore, effective methods for involving different organizations and user groups in the FFE of innovation are needed.

OBJECTIVE

The aim of this study was to manage the FFE of a collaborative, open innovation (OI) process, to define a software system supporting seniors' physical activity (PA) by applying a framework of methods from software requirements engineering (RE) to elicit and analyze needs and requirements of users and stakeholders, as well as the context in which the system should be used.

METHODS

Needs and requirements of three future user groups were explored through individual- and focus group interviews. Requirements were categorized and analyzed in a workshop with a multidisciplinary team: a system overview was produced by conceptual modelling using elicited functional requirements; high-level non-functional requirements were negotiated and prioritized. Scenario descriptions of system's supportive roles in different phases of a behavioral change process were developed.

RESULTS

User-centered RE methods were successfully used to define a system and a high-level requirements description was developed based on needs and requirements from three identified user groups. The system aimed to support seniors' motivation for PA and contained four complementary sub-systems. The outcome of the study was a Concept of Operations (ConOps) document that specified the high-level system requirements in a way that was understandable for stakeholders. This document was used both to identify and recruit suitable industrial partners for the following open innovation development and to facilitate communication and collaboration in the innovation process.

CONCLUSIONS

Applying software RE methods and involving user groups in the early phases of OI can contribute to the development of new concepts that meet complex real-world requirements. Different user groups can complement each other in conveying needs and requirements from which systems can be designed. Empirical studies applying and exploring different methods used to define new e-health solutions can contribute with valuable knowledge about handling innovation FFE.

Performance and Characteristics of Wearable Sensor Systems Discriminating and Classifying Older Adults According to Fall Risk: A Systematic Review

Sensor-based fall risk assessment (SFRA) utilizes wearable sensors for monitoring individuals’ motions in fall risk assessment tasks. Previous SFRA reviews recommend methodological improvements to better support the use of SFRA in clinical practice. This systematic review aimed to investigate the existing evidence of SFRA (discriminative capability, classification performance) and methodological factors (study design, samples, sensor features, and model validation) contributing to the risk of bias. The review was conducted according to recommended guidelines and 33 of 389 screened records were eligible for inclusion. Evidence of SFRA was identified: several sensor features and three classification models differed significantly between groups with different fall risk (mostly fallers/non-fallers). Moreover, classification performance corresponding the AUCs of at least 0.74 and/or accuracies of at least 84% were obtained from sensor features in six studies and from classification models in seven studies. Specificity was at least as high as sensitivity among studies reporting both values. Insufficient use of prospective design, small sample size, low in-sample inclusion of participants with elevated fall risk, high amounts and low degree of consensus in used features, and limited use of recommended model validation methods were identified in the included studies. Hence, future SFRA research should further reduce risk of bias by continuously improving methodology.

The Effect of Mixed Reality Technologies for Falls Prevention Among Older Adults: Systematic Review and Meta-analysis

BACKGROUND

Falling is one of the most common and serious age-related issues, and falls can significantly impair the quality of life of older adults. Approximately one-third of people over 65 experience a fall annually. Previous research has shown that physical exercise could help reduce falls among older adults and improve their health. However, older adults often find it challenging to follow and adhere to physical exercise programs. Interventions using mixed reality (MR) technology could help address these issues. MR combines artificial augmented computer-generated elements with the real world. It has frequently been used for training and rehabilitation purposes.

OBJECTIVE

The aim of this systematic literature review and meta-analysis was to investigate the use of the full spectrum of MR technologies for fall prevention intervention and summarize evidence of the effectiveness of this approach.

METHODS

In our qualitative synthesis, we analyzed a number of features of the selected studies, including aim, type of exercise, technology used for intervention, study sample size, participant demographics and history of falls, study design, involvement of health professionals or caregivers, duration and frequency of the intervention, study outcome measures, and results of the study. To systematically assess the results of the selected studies and identify the common effect of MR interventions, a meta-analysis was performed.

RESULTS

Seven databases were searched, and the initial search yielded 5838 results. With the considered inclusion and exclusion criteria, 21 studies were included in the qualitative synthesis and 12 were included in meta-analysis. The majority of studies demonstrated a positive effect of an MR intervention on fall risk factors among older participants. The meta-analysis demonstrated a statistically significant difference in Berg Balance Scale score between the intervention and control groups (ES: 0.564; 95% CI 0.246-0.882; P<.001) with heterogeneity statistics of I2=54.9% and Q=17.74 (P=.02), and a statistical difference in Timed Up and Go test scores between the intervention and control groups (ES: 0.318; 95% CI 0.025-0.662; P<.001) with heterogeneity statistics of I2=77.6% and Q=44.63 (P<.001). The corresponding funnel plot and the Egger test for small-study effects (P=.76 and P=.11 for Berg Balance Scale and Timed Up and Go, respectively) indicate that a minor publication bias in the studies might be present in the Berg Balance Scale results.

CONCLUSIONS

The literature review and meta-analysis demonstrate that the use of MR interventions can have a positive effect on physical functions in the elderly. MR has the potential to help older users perform physical exercises that could improve their health conditions. However, more research on the effect of MR fall prevention interventions should be conducted with special focus given to MR usability issues.

Use of technology and social media in dementia care: Current and future directions

As the population across the globe continues to dramatically increase, the prevalence of cognitive impairment and dementia will inevitably increase as well, placing increasing burden on families and health care systems. Technological advancements over the past decade provide potential benefit in not only relieving caregiver burden of caring for a loved one with dementia, but also enables individuals with dementia to age in place. Technological devices have served to improve functioning, tracking and mobility. Similarly, smartphones, tablets and the ubiquitous world wide web have facilitated the dissemination of health information to previously hard to reach populations largely through use of various social media platforms. In this review, we discuss the current and future uses of technology via devices and social media to promote healthy aging in individuals with dementia, and also limitations and challenges to consider in the future.

Assessing elderly's functional balance and mobility via analyzing data from waist-mounted tri-axial wearable accelerometers in timed up and go tests

Background

Poor balance has been cited as one of the key causal factors of falls. Timely detection of balance impairment can help identify the elderly prone to falls and also trigger early interventions to prevent them. The goal of this study was to develop a surrogate approach for assessing elderly’s functional balance based on Short Form Berg Balance Scale (SFBBS) score.

Methods

Data were collected from a waist-mounted tri-axial accelerometer while participants performed a timed up and go test. Clinically relevant variables were extracted from the segmented accelerometer signals for fitting SFBBS predictive models. Regularized regression together with random-shuffle-split cross-validation was used to facilitate the development of the predictive models for automatic balance estimation.

Results

Eighty-five community-dwelling older adults (72.12 ± 6.99 year) participated in our study. Our results demonstrated that combined clinical and sensor-based variables, together with regularized regression and cross-validation, achieved moderate-high predictive accuracy of SFBBS scores (mean MAE = 2.01 and mean RMSE = 2.55). Step length, gender, gait speed and linear acceleration variables describe the motor coordination were identified as significantly contributed variables of balance estimation. The predictive model also showed moderate-high discriminations in classifying the risk levels in the performance of three balance assessment motions in terms of AUC values of 0.72, 0.79 and 0.76 respectively.

Conclusions

The study presented a feasible option for quantitatively accurate, objectively measured, and unobtrusively collected functional balance assessment at the point-of-care or home environment. It also provided clinicians and elderly with stable and sensitive biomarkers for long-term monitoring of functional balance.

The Association of Falls with Instability: An Analysis of Perceptions and Expectations toward the Use of Fall Detection Devices Among Older Adults in Malaysia

Background: Falls are a significant incident among older adults affecting one in every three individuals aged 65 and over. Fall risk increases with age and other factors, namely instability. Recent studies on the use of fall detection devices in the Malaysian community are scarce, despite the necessity to use them. Therefore, this study aimed to investigate the association between the prevalence of falls with instability. This study also presents a survey that explores older adults' perceptions and expectations toward fall detection devices.

Methods: A cross-sectional survey was conducted involving 336 community-dwelling older adults aged 50 years and older; based on randomly selected participants. Data were analyzed using quantitative descriptive analysis. Chi-square test was conducted to investigate the associations between self-reported falls with instability, demographic and walking characteristics. Additionally, older adults' perceptions and expectations concerning the use of fall detection devices in their daily lives were explored.

Results: The prevalence of falls was 28.9%, where one-quarter of older adults fell at least once in the past 6 months. Participants aged 70 years and older have a higher fall percentage than other groups. The prevalence of falls was significantly associated with instability, age, and walking characteristics. Around 70% of the participants reported having instability issues, of which over half of them fell at least once within 6 months. Almost 65% of the participants have a definite interest in using a fall detection device. Survey results revealed that the most expected features for a fall detection device include: user-friendly, followed by affordably priced, and accurate.

Conclusions: The prevalence of falls in community-dwelling older adults is significantly associated with instability. Positive perceptions and informative expectations will be used to develop an enhanced fall detection incorporating balance monitoring system. Our findings demonstrate the need to extend the fall detection device features aiming for fall prevention intervention.

Directing and Orienting ICT Healthcare Solutions to Address the Needs of the Aging Population

BACKGROUND

With an aging population, it is essential to maintain good health and autonomy for as long as possible. Instead of hospitalisation or institutionalisation, older people with chronic conditions can be assisted in their own home with numerous "smart" devices that support them in their activities of daily living, manage their medical conditions, and prevent fall incidents. Information and Communication Technology (ICT) solutions facilitate the monitoring and management of older people's health to improve quality of life and physical activity with a decline in caregivers' burden.

METHOD

The aim of this paper was to conduct a systematic literature review to analyse the state of the art of ICT solutions for older people with chronic conditions, and the impact of these solutions on their quality of life from a biomedical perspective.

RESULTS

By analysing the literature on the available ICT proposals, it is shown that different approaches have been deployed by noticing that the more cross-interventions are merged then the better the results are, but there is still no evidence of the effects of ICT solutions on older people's health outcomes. Furthermore, there are still unresolved ethical and legal issues.

CONCLUSION

While there has been much research and development in healthcare ICT solutions for the aging population, ICT solutions still need significant development in order to be user-oriented, affordable, and to manage chronic conditions in the aging wider population.

Fall prevention programs for culturally and linguistically diverse groups: program provider perspectives

Objectives: Older people from culturally and linguistically diverse (CALD) backgrounds are one of the fastest growing and rapidly ageing population segments in Australia. This qualitative study aims to explore the experiences, needs and challenges that individual program providers encountered in implementing and delivering a fall prevention program for CALD groups and meeting the linguistic, cultural and contextual needs of the program participants.Design: Semi-structured in-depth interviews were conducted with a convenience sample of 24 program providers implementing, delivering or supporting fall prevention programs including Stepping On for CALD groups. Interview transcripts were analysed using thematic analysis.Results: Two major themes emerged: (1) extra layers of complexity are needed in program planning, delivery, recruitment and enabling participation of older people from CALD background and (2) program leaders 'going the extra mile' influences success of the program. Complexity included accommodating the linguistic and sociocultural needs in planning the programs, knowing and using the 'right way' to reach and deliver the program to CALD groups and understanding the nuances of facilitating program participation. While it was important to ensure the acceptability and accessibility of the program for the older people from diverse CALD communities, it was the drive and determination of the program leader and their striving for cultural relevance that made the program possible. Sustainability and wider implementation requires unique support and additional resources.Conclusion: These findings can be used by program providers, policy-makers and health researchers to improve the capacity of fall prevention programs to better respond to the growing diversity in needs and preferences among older populations in Australia and internationally.

Staffing Utilization and Fall Prevention With an Electronic Surveillance Video System: A Randomized Controlled Study

BACKGROUND

There is limited research addressing how to optimize both staffing and patient outcomes with the use of technology to reduce falls during hospitalization.

PURPOSE

We compared the effects of 2 staffing patterns in conjunction with the use of an electronic surveillance system on patient falls on an inpatient medical unit.

METHODS

Study participants were randomized to receive electronic surveillance system monitoring with a dedicated rounder or electronic surveillance system without a dedicated rounder. Falls during the study period were analyzed.

RESULTS

Of 1032 patients, there were 8 falls during the 3-month study. Six falls occurred in the intervention group, with no rounder, and 2 occurred in the group with a dedicated rounder. The data showed no statistical significance but had clinical implications.

CONCLUSION

In response to our findings, the dedicated rounder will function as a mobility technician, providing support to our nursing staff and a resource for fall risk patients.

Evaluating Balance Recovery Techniques for Users Wearing Head-Mounted Display in VR

Room-scale 3D position tracking enables users to explore a virtual environment by physically walking, which improves comfort and the level of immersion. However, when users walk with their eyesight blocked by a head-mounted display, they may unexpectedly lose their balance and fall if they bump into real-world obstacles or unintentionally shift their center of mass outside the margin of stability. This paper evaluates balance recovery methods and intervention timing during the use of VR with the assumption that the onset of a fall is given. Our experiment followed the tether-release protocol during clinical research and induced a fall while a subject was engaged in a secondary 3D object selection task. The experiment employed a two-by-two design that evaluated two assistive techniques, i.e., video-see-through and auditory warning at two different timings, i.e., at fall onset and 500ms prior to fall onset. The data from 17 subjects showed that video-see-through triggered 500 ms before the onset of fall can effectively help users recover from falls. Surprisingly, video-see-through at fall onset has a significant negative impact on balance recovery and produces similar results to those of the baseline condition (no intervention).

Technology Utilization in Fall Prevention

ABSTRACT

Falls, defined as unplanned descents to the floor with or without injury to an individual, remain to be one of the most challenging health conditions. Fall rate is a key quality metric of acute care hospitals, rehabilitation settings, and long-term care facilities. Fall prevention policies with proper implementation have been the focus of surveys by regulatory bodies, including The Joint Commission and the Centers for Medicare and Medicaid Services, for all healthcare settings. Since October 2008, the Centers for Medicare and Medicaid Services has stopped reimbursing hospitals for the costs related to patient falls, shifting the accountability for fall prevention to the healthcare providers. Research shows that almost one-third of falls can be prevented and extensive fall prevention interventions exist. Recently, technology-based applications have been introduced in healthcare to obtain superior patient care outcomes and experience via efficiency, access, and reliability. Several areas in fall prevention deploy technology, including predictive and prescriptive analytics using big data, video monitoring and alarm technology, wearable sensors, exergame and virtual reality, robotics in home environment assessment, and personal coaching. This review discusses an overview of these technology-based applications in various settings, focusing on the outcomes of fall reductions, cost, and other benefits.

Acceptance of a Virtual Reality Headset Designed for Fall Prevention in Older Adults: Questionnaire Study

BACKGROUND

Falls are a common phenomenon among people aged 65 and older and affect older adults' health, quality of life, and autonomy. Technology-based intervention programs are designed to prevent the occurrence of falls and their effectiveness often surpasses that of more conventional programs. However, to be effective, these programs must first be accepted by seniors.

OBJECTIVE

Based on the technology acceptance model, this study aimed to examine the acceptance among older adults before a first use of a virtual reality headset (VRH) used in an intervention program designed to prevent falls.

METHODS

A sample of 271 French older adults (mean age 73.69 years, SD 6.37 years) voluntarily and anonymously filled out a questionnaire containing the focal constructs (perceived usefulness, perceived enjoyment, perceived ease of use, intention to use, fall-related self-efficacy, and self-avoidance goals) adapted to the VRH, which was designed to prevent falls.

RESULTS

The results of the structural equation modeling analysis showed that intention to use the VRH was positively predicted by perceived usefulness, perceived enjoyment, and perceived ease of use. Perceived usefulness of the VRH was also negatively predicted by fall-related self-efficacy (ie, the perceived level of confidence of an individual when performing daily activities without falling) and positively predicted by self-avoidance goals (ie, participating in a physical activity to avoid physical regression).

CONCLUSIONS

A better understanding of the initial acceptance among older adults of this VRH is the first step to involving older adults in intervention programs designed to prevent falls using this kind of device.

Estimating Postural Stability Using Improved Permutation Entropy via TUG Accelerometer Data for Community-Dwelling Elderly People

To develop an effective fall prevention program, clinicians must first identify the elderly people at risk of falling and then take the most appropriate interventions to reduce or eliminate preventable falls. Employing feature selection to establish effective decision making can thus assist in the identification of a patient's fall risk from limited data. This work therefore aims to supplement professional timed up and go assessment methods using sensor technology, entropy analysis, and statistical analysis. The results showed the different approach of applying logistic regression analysis to the inertial data on a fall-risk scale to allow medical practitioners to predict for high-risk patients. Logistic regression was also used to automatically select feature values and clinical judgment methods to explore the differences in decision making. We also calculate the area under the receiver-operating characteristic curve (AUC). Results indicated that permutation entropy and statistical features provided the best AUC values (all above 0.9), and false positives were avoided. Additionally, the weighted-permutation entropy/statistical features test has a relatively good agreement rate with the short-form Berg balance scale when classifying patients as being at risk. Therefore, the proposed methodology can provide decision-makers with a more accurate way to classify fall risk in elderly people.

Web-based home-hazard modification app for falls prevention: the views of those at risk of falling and their carers

Purpose

The purpose of the study is to assess the usability and acceptability of FallCheck, a Web app that allows users to complete home-hazard assessments within their own home, with a group of people at risk of falling and their carers.

Design/methodology/approach

This mixed method study used an online survey followed by semi-structured telephone interviews to collect both qualitative and quantitative data. A Think-Aloud study was used to test usability of the Web app through structured tasks.

Findings

Findings showed that FallCheck was easy to use with few usability issues. The Web app was deemed appropriate to use by people at risk of falling (young or old) or by carers if appropriate. The depth of knowledge provision and breadth of content was acceptable, and many participants reported subsequently making changes to their home environment to reduce their risk of falling. Overall, the majority of participants reported feelings of improved confidence and safety with an increased awareness of fall risks and a reduction in fear of falling at home.

Practical implications

FallCheck has good acceptability and usability with people at risk of falling and their carers and has the potential to improve access to home-hazard assessment and affect behavioural change regarding fall risk hazards and behaviour.

Originality/value

This study describes successful use of an app that may be helpful in identifying home-hazards and making changes to reduce risk of falls, particularly in the absence of occupational therapy intervention and has the potential for integration into falls care pathways.

Co-Creation with Older Adults to Improve User-Experience of a Smartphone Self-Test Application to Assess Balance Function

This co-creation study aimed to develop a smartphone self-test application for balance and leg strength in collaboration between older adults and the research team. The paper describes older participants’ preferences for, and their contribution to, the application design. Technology to assess movements is available in smartphones with built-in sensors, and one of the challenges is to develop a valuable self-test for older adults. The participants contributed to the design of the application’s instructions and user interface. Multiple data collection methods were used: user-test with Think aloud method, mock-ups, homework assignment as co-researcher, audio and video recordings. Qualitative content analysis with a deductive-inductive approach was used, guided by the Optimized Honeycomb model for user experience (UX) as a categorization matrix. The analysis resulted in 17 subcategories within the seven facets of the UX Honeycomb model (findable, accessible, usable, desirable, credible, useful, and valuable), and describes the older participants’ preferences and experiences. The main results were participants’ desire to know why, to get clear and appropriate information, and expectations of the self-test to be useful. It was feasible and valuable to develop the self-test application in co-creation with the intended user-group, in order to get direct feedback and suggestions for the development.

Wearable Stretch Sensors for Human Movement Monitoring and Fall Detection in Ergonomics

Wearable sensors are beneficial for continuous health monitoring, movement analysis, rehabilitation, evaluation of human performance, and for fall detection. Wearable stretch sensors are increasingly being used for human movement monitoring. Additionally, falls are one of the leading causes of both fatal and nonfatal injuries in the workplace. The use of wearable technology in the workplace could be a successful solution for human movement monitoring and fall detection, especially for high fall-risk occupations. This paper provides an in-depth review of different wearable stretch sensors and summarizes the need for wearable technology in the field of ergonomics and the current wearable devices used for fall detection. Additionally, the paper proposes the use of soft-robotic-stretch (SRS) sensors for human movement monitoring and fall detection. This paper also recapitulates the findings of a series of five published manuscripts from ongoing research that are published as Parts I to V of “Closing the Wearable Gap” journal articles that discuss the design and development of a foot and ankle wearable device using SRS sensors that can be used for fall detection. The use of SRS sensors in fall detection, its current limitations, and challenges for adoption in human factors and ergonomics are also discussed.

Effectiveness of a self-managed digital exercise programme to prevent falls in older community-dwelling adults: study protocol for the Safe Step randomised controlled trial

INTRODUCTION

Exercise interventions have a strong evidence base for falls prevention. However, exercise can be challenging to implement and often has limited reach and poor adherence. Digital technology provides opportunities for both increased access to the intervention and support over time. Further knowledge needs to be gained regarding the effectiveness of completely self-managed digital exercise interventions. The main objective of this study is to compare the effectiveness of a self-managed digital exercise programme, Safe Step, in combination with monthly educational videos with educational videos alone, on falls over 1 year in older community-dwelling adults.

METHODS AND ANALYSIS

A two-arm parallel randomised controlled trial will be conducted with at least 1400 community-living older adults (70+ years) who experience impaired balance. Participants will be recruited throughout Sweden with enrolment through the project website. They will be randomly allocated to either the Safe Step exercise programme with additional monthly educational videos about healthy ageing and fall prevention, or the monthly education videos alone. Participants receiving the exercise intervention will be asked to exercise at home for at least 30 min, 3 times/week with support of the Safe Step application. The primary outcome will be rate of falls (fall per person year). Participants will keep a fall calendar and report falls at the end of each month through a digital questionnaire. Further assessments of secondary outcomes will be made through self-reported questionnaires and a self-test of 30 s chair stand test at baseline and 3, 6, 9 and 12 months after study start. Data will be analysed according to the intention-to-treat principle.

ETHICS AND DISSEMINATION

Ethical approval was obtained by The Regional Ethical Review Board in Umeå (Dnr 2018/433-31). Findings will be disseminated through the project web-site, peer-reviewed journals, national and international conferences and through senior citizen organisations' newsletters.

TRIAL REGISTRATION NUMBER

NCT03963570.

[Information technology and eHealth to improve patient safety]

Patient safety is a key element of high-quality healthcare. Digitalization, new eHealth applications and data-based algorithms have high potential to make a significant contribution. This article presents current technological developments along a simplified patient journey from emergency medical triage, diagnosis and therapy to follow-up. The technical interventions are highly diverse and mostly accompanied by a low level of evidence, since most of them are from single academic projects or start-ups. Although there should be no doubt that technology is an important instrument for increasing patient safety, new technologies also involve new risks. Furthermore, technical measures must always be embedded in an overall concept of organizational measures, adequate education, training and accompanying research in order to generate the highest possible benefits and lowest possible risks.

Factors predicting older Adults' attitudes toward and intentions to use stair mobility assistive designs at home

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Perceived usefulness predicts attitudes and intentions to use stair mobility products.

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Aesthetics, fear of falling, and person-environment fit influence product acceptance.

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Age and living with others negatively impact attitude toward stair mobility products.

Home modifications that increase stair accessibility of existing housing stock are significant for older adults who want to age in place. This sequential mixed-methods study investigated older adults’ attitudes toward and intentions to use currently available stair mobility assistive design features, and explored which factors influence these attitudes and intentions to use. The data were collected through a cross-sectional survey of community-dwelling 50 + adults from Southwest Virginia (n = 89) and a focus group (n = 15) in 2018. The survey questionnaire was based on a modified version of the Technology Acceptance Model, and focused on three stair mobility assistive design products representative of varying costs, and a range of mobility challenges: half-steps, StairSteady handrail, and stairlift. Ordinal regression analyses indicated that perceived usefulness consistently predicts older adults’ attitudes and intentions to use the three examined stair mobility products. The other factors associated with attitudes and willingness to use the products are dependent on some degree to the examined mobility device. Older age and presence of others in the household negatively influenced attitudes toward stair mobility products. Product aesthetics/unobtrusiveness, fear of falling, and person-environment fit are the three themes emerged from the focus group data analysis as the factors that most influence community-dwelling older adults’ attitudes and intention to use stair-mobility assistive features. The findings have implications for design professionals, as they underscore the need for avoiding an institutional look in residential designs, specifying products with high customizability for user needs and preferences, and involvement of users in the decision-making processes.

Promoting Fall Prevention among Community Dwelling Older Adults through ActivLife: a Physical and Social Activation

Falls have been recognized as the second leading cause of injury or death for older adults. The related economic burden caused by fall related injuries is not negligible. Earlier research has demonstrated that regular participation in appropriate prescribed physical activity by improving upper and lower limb strength, balance, coordination, transfer skills, and reaction to environmental hazards can lower the risk for falls and fall-related fractures and other injuries. Conversely, physical inactivity can significantly double the risk of developing a disability, which will affect mobility as well as the ability to perform even the most basic activities of daily life, therefore, ultimately increases the older adults’ risk for falls.

This paper first presents a technological solution ActivLife that aims at preventing older adults from falling through practicing physical training in a safe and playful manner, followed by a randomized controlled study with 43 older adults with an average age of 77 for a period of 16 weeks in a social activation center het Ontmoet en Groethuys in Eindhoven, the Netherlands to demonstrate to what extent ActivLife could help to prevent falling among older adults.

Closing the Wearable Gap—Part III: Use of Stretch Sensors in Detecting Ankle Joint Kinematics During Unexpected and Expected Slip and Trip Perturbations

Background: An induced loss of balance resulting from a postural perturbation has been reported as the primary source for postural instability leading to falls. Hence; early detection of postural instability with novel wearable sensor-based measures may aid in reducing falls and fall-related injuries. The purpose of the study was to validate the use of a stretchable soft robotic sensor (SRS) to detect ankle joint kinematics during both unexpected and expected slip and trip perturbations. Methods: Ten participants (age: 23.7 ± 3.13 years; height: 170.47 ± 8.21 cm; mass: 82.86 ± 23.4 kg) experienced a counterbalanced exposure of an unexpected slip, an unexpected trip, an expected slip, and an expected trip using treadmill perturbations. Ankle joint kinematics for dorsiflexion and plantarflexion were quantified using three-dimensional (3D) motion capture through changes in ankle joint range of motion and using the SRS through changes in capacitance when stretched due to ankle movements during the perturbations. Results: A greater R-squared and lower root mean square error in the linear regression model was observed in comparing ankle joint kinematics data from motion capture with stretch sensors. Conclusions: Results from the study demonstrated that 71.25% of the trials exhibited a minimal error of less than 4.0 degrees difference from the motion capture system and a greater than 0.60 R-squared value in the linear model; suggesting a moderate to high accuracy and minimal errors in comparing SRS to a motion capture system. Findings indicate that the stretch sensors could be a feasible option in detecting ankle joint kinematics during slips and trips.

Can smartphone technology be used to support an effective home exercise intervention to prevent falls amongst community dwelling older adults?: the TOGETHER feasibility RCT study protocol

INTRODUCTION

Falls have major implications for quality of life, independence and cost to the health service. Strength and balance training has been found to be effective in reducing the rate/risk of falls, as long as there is adequate fidelity to the evidence-based programme. Health services are often unable to deliver the evidence-based dose of exercise and older adults do not always sufficiently adhere to their programme to gain full outcomes. Smartphone technology based on behaviour-change theory has been used to support healthy lifestyles, but not falls prevention exercise. This feasibility trial will explore whether smartphone technology can support patients to better adhere to an evidence-based rehabilitation programme and test study procedures/outcome measures.

METHODS AND ANALYSIS

A two-arm, pragmatic feasibility randomised controlled trial will be conducted with health services in Manchester, UK. Seventy-two patients aged 50+years eligible for a falls rehabilitation exercise programme from two community services will receive: (1) standard service with a smartphone for outcome measurement only or (2) standard service plus a smartphone including the motivational smartphone app. The primary outcome is feasibility of the intervention, study design and procedures. The secondary outcome is to compare standard outcome measures for falls, function and adherence to instrumented versions collected using smartphone. Outcome measures collected include balance, function, falls, strength, fear of falling, health-related quality of life, resource use and adherence. Outcomes are measured at baseline, 3 and 6-month post-randomisation. Interviews/focus groups with health professionals and participants further explore feasibility of the technology and trial procedures. Primarily analyses will be descriptive.

ETHICS AND DISSEMINATION

The study protocol is approved by North West Greater Manchester East Research Ethics Committee (Rec ref:18/NW/0457, 9/07/2018). User groups and patient representatives were consulted to inform trial design, and are involved in study recruitment. Results will be reported at conferences and in peer-reviewed publications. A dissemination event will be held in Manchester to present the results of the trial. The protocol adheres to the recommended Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklist.

TRIAL REGISTRATION NUMBER

ISRCTN12830220; Pre-results.

Mobile three-dimensional visualisation technologies for clinician-led fall prevention assessments

The assistive equipment provision process is routinely carried out with patients to mitigate fall risk factors via the fitment of assistive equipment within the home. However, currently, over 50% of assistive equipment is abandoned by the patients due to poor fit between the patient and the assistive equipment. This paper explores clinician perceptions of an early stage three-dimensional measurement aid prototype, which provides enhanced assistive equipment provision process guidance to clinicians. Ten occupational therapists trialled the three-dimensional measurement aid prototype application; think-aloud and semi-structured interview data was collected. Usability was measured with the System Usability Scale. Participants scored three-dimensional measurement aid prototype as 'excellent' and agreed strongly with items relating to the usability and learnability of the application. The qualitative analysis identified opportunities for improving existing practice, including, improved interpretation/recording measurements; enhanced collaborative practice within the assistive equipment provision process. Future research is needed to determine the clinical utility of this application compared with two-dimensional counterpart paper-based guidance leaflets.

Technology-Based Motivation Support for Seniors' Physical Activity-A Qualitative Study on Seniors' and Health Care Professionals' Views

This paper investigates seniors’ and health care professionals’ (HCPs) perceptions on needed contributions and qualities of digital technology-based motivation support for seniors’ physical activity (PA). Seniors and HCPs expressed their views in focus groups, which were analyzed separately by inductive content analysis. Similarities and differences in seniors’ and HCPs’ views were identified through thematic analysis of qualitative results from both focus groups. This article’s main findings are that both seniors and HCPs believed digital technology should support and make PA more enjoyable in ways to strengthen seniors’ control and well-being. However, seniors emphasized support for social interaction, while HCPs also requested support for increasing seniors’ insight into PA and for facilitating their dialogue with seniors. Conclusions to be drawn are that seniors and HPCs shared overall views on digital technology’s main contributions but had different perspectives on how those contributions could be obtained. This highlights the importance of the early identification of user groups and exploration of their different needs when developing new solutions. Moreover, seniors’ and HCPs’ perceptions included aspects relevant for personal motivation, technology acceptance, and PA behavioral change according to self-determination theory, unified theory of acceptance and use of technology, and behavioral change techniques for increasing PA.