Investigating the relationship between sagittal spinal curvature and fall incidence and fall risk among elderly nursing home residents.

Designing appropriate diagnostic and treatment methods to reduce fall risk and improve quality of life, as well as reduce the cost of care in elderlies. Our findings have potential for early diagnosis of those with a high probability of falling based on fairly simple clinical measures of hyperkyphosis, forward head, and lordosis. INTRODUCTION: Poor balance is an underlying cause of falling in the elderly, for which a change in the natural curvature of the spine plays a major role. Little is known about the relationship between spinal curvatures and fall incidence in this population. We primarily aimed to investigate the relationship between sagittal plane spinal curvatures and fall incidence over 1 year among nursing facility residents. Secondarily, we aim to determine associations of sagittal plane spinal curvatures with participants' perception of fall risk and balance capability. METHODS: Participants (100 residents mean age 70.17 ± 6.01 years) underwent standing measures of sagittal plane spinal curvatures (flexible ruler technique) and forward displacement of the head relative to the cervical spine. The Tinetti Performance Oriented Mobility Assessment (POMA) and Fall Efficacy Scale assessed participants' perception of balance and fear of falling. Incident falls were self-reported monthly and tracked across 1 year. Spearman's correlations and logistic regression evaluated associations between fall incidence and spinal curvature. Predictive performance of spinal curvature and fall risk was determined by the corresponding ROC for defining a cut-off for variables of spinal curvature and fall risk indicators. RESULTS: Predictive performance of spinal curvature and fall risk factors indicated 84% and 77% of participants were correctly classified using models of kyphosis and head angle, respectively. CONCLUSIONS: Our study adds new data on spinal curvatures and incident falls among nursing facility residents. Efforts are needed to intervene to counter progression of spinal curvatures and improve fall prevention practices.

Geriatric Dermatologic Surgery Part II: Peri and intraoperative considerations in the geriatric dermatologic surgery patient.

Geriatric patients compose a growing proportion of the dermatologic surgical population. Dermatologists and dermatologic surgeons should be cognizant of the unique physiologic considerations that accompany this group to deliver highly effective care. The purpose of this article is to discuss the unique preoperative, intraoperative, and postoperative considerations geriatric patients present with to provide goal-concordant care. Preoperative considerations include medication optimization and anxiolysis. Intraoperative considerations such as fall-risk assessment and prevention, sundowning, familial support, and pharmacologic interactions will be discussed. Lastly, effective methods for optimizing post-operative wound care, home care, and follow up are reviewed.

Effects of medication management in geriatric patients who have fallen: results of the EMMA mixed-methods study.

BACKGROUND: comprehensive medication management (CMM) can reduce medication-related risks of falling. However, knowledge about inter-individual treatment effects and patient-related barriers remains scarce. OBJECTIVE: to gain in-depth insights into how geriatric patients who have fallen view their medication-related risks of falling and to identify effects and barriers of a CMM in preventing falls. DESIGN: complementary mixed-methods pre-post study, based on an embedded quasi-experimental model. SETTING: geriatric fracture centre. METHODS: qualitative, semi-structured interviews framed the CMM intervention, including a follow-up period of 12 weeks. Interviews explored themes of falling, medication-related risks, post-discharge acceptability and sustainability of interventions using qualitative content analysis. Optimisation of pharmacotherapy was assessed via changes in the weighted and summated Medication Appropriateness Index (MAI) score, number of fall-risk-increasing drugs (FRID) and potentially inappropriate medications (PIM) according to the Fit fOR The Aged and PRISCUS lists using parametric testing. RESULTS: thirty community-dwelling patients aged ≥65 years, taking ≥5 drugs and admitted after an injurious fall were recruited. The MAI was significantly reduced, but number of FRID and PIM remained largely unchanged. Many patients were open to medication reduction/discontinuation, but expressed fear when it came to their personal medication. Psychosocial issues and pain increased the number of indications. Safe alternatives for FRID were frequently not available. Psychosocial burden of living alone, fear, lack of supportive care and insomnia increased after discharge. CONCLUSION: as patients' individual attitudes towards trauma and medication were not predictable, an individual and longitudinal CMM is required. A standardised approach is not helpful in this population.

Topic evolution before fall incidents in new fallers through natural language processing of general practitioners' clinical notes.

BACKGROUND: Falls involve dynamic risk factors that change over time, but most studies on fall-risk factors are cross-sectional and do not capture this temporal aspect. The longitudinal clinical notes within electronic health records (EHR) provide an opportunity to analyse fall risk factor trajectories through Natural Language Processing techniques, specifically dynamic topic modelling (DTM). This study aims to uncover fall-related topics for new fallers and track their evolving trends leading up to falls. METHODS: This case-cohort study utilised primary care EHR data covering information on older adults between 2016 and 2019. Cases were individuals who fell in 2019 but had no falls in the preceding three years (2016-18). The control group was randomly sampled individuals, with similar size to the cases group, who did not endure falls during the whole study follow-up period. We applied DTM on the clinical notes collected between 2016 and 2018. We compared the trend lines of the case and control groups using the slopes, which indicate direction and steepness of the change over time. RESULTS: A total of 2,384 fallers (cases) and an equal number of controls were included. We identified 25 topics that showed significant differences in trends between the case and control groups. Topics such as medications, renal care, family caregivers, hospital admission/discharge and referral/streamlining diagnostic pathways exhibited a consistent increase in steepness over time within the cases group before the occurrence of falls. CONCLUSIONS: Early recognition of health conditions demanding care is crucial for applying proactive and comprehensive multifactorial assessments that address underlying causes, ultimately reducing falls and fall-related injuries.

The Fracture Phenotypes in Women and Men of 50 Years and Older with a Recent Clinical Fracture.

PURPOSE OF REVIEW: We review the literature about patients 50 years and older with a recent clinical fracture for the presence of skeletal and extra-skeletal risks, their perspectives of imminent subsequent fracture, falls, mortality, and other risks, and on the role of the fracture liaison service (FLS) for timely secondary fracture prevention. RECENT FINDINGS: Patients with a recent clinical fracture present with heterogeneous patterns of bone-, fall-, and comorbidity-related risks. Short-term perspectives include bone loss, increased risk of fractures, falls, and mortality, and a decrease in physical performance and quality of life. Combined evaluation of bone, fall risk, and the presence of associated comorbidities contributes to treatment strategies. Since fractures are related to interactions of bone-, fall-, and comorbidity-related risks, there is no one-single-discipline-fits-all approach but a need for a multidisciplinary approach at the FLS to consider all phenotypes for evaluation and treatment in an individual patient.

Long-Term Effects and Impressions of Minimal Footwear in Older Adults.

INTRODUCTION: Foot pathologies can lead to difficulty walking and falls in older adults. Intrinsic foot muscles contribute to the structural support and alignment of the foot and provide somatosensory input from the ground. Minimally cushioned footwear may naturally strengthen intrinsic foot muscles and enhance sensory input to the foot; however, these effects are largely unknown in older adults. Further, there is little evidence regarding the prescription of minimal footwear and the perceptions of this footwear by older adults. METHODS: Twenty-four adults age ≥65 volunteered to use minimal footwear for prescribed times during daily activities for 16 weeks. The cross-sectional area (CSA) of 5 intrinsic foot muscles was measured using ultrasound imaging at baseline, 8 weeks, and 16 weeks. Semi-structured interviews were recorded regarding participants' impressions of the footwear, the progressive wear schedule, the footwear's effects on orthopedic-related pain, balance, and foot awareness/sensation. RESULTS: Across the cohort, there was no significant difference in CSA of the 5 muscles after 16 weeks of minimal footwear use. Thirteen participants had clinically meaningful increased CSA of the abductor hallucis muscle (Abh). These positive responders had no significant differences in age, grip strength, foot structure, or fall risk scores compared to participants with little to no CSA change. Interview results indicated a generally positive experience with minimal footwear for 68.1% of the cohort. A large percentage of the cohort reported no difficulty with the progressive wear schedule (77.2%), no aggravation of preexisting conditions and no new pain (77.2%), improved balance (63.6%), and improved foot awareness/sensation (72.7%) with minimal footwear use. The progressive wear schedule was perceived as inconvenient by some in the first few weeks (22.8%), but resulted in mild to no adverse effects when followed as prescribed. CONCLUSION: Sixteen weeks of progressive minimal footwear use in older adults did not lead to changes in intrinsic foot muscle CSA; however, half of the cohort had clinically meaningful increased CSA in the Abh muscle. It is unclear what individual qualities were associated with this positive response. Older adults reported generally positive experiences with minimal footwear with self-reported improvements in balance and foot awareness/sensation. The wear schedule may have been too conservative or not long enough to produce foot muscle hypertrophy, but subjective reports suggest beneficial neuromuscular adaptations and sensory changes occurred. Future research may need a greater length of time and larger samples to further determine the effects of long-term minimal footwear use in older adults.

Quality evaluation of the usefulness of an emergency department fall risk assessment tool.

INTRODUCTION: Falls that occur within a hospital setting are difficult to predict, however, are preventable adverse events with the potential to negatively impact patient care. Falls have the potential to cause serious or fatal injuries and may increase patient morbidity. Many hospitals utilize fall "predictor tools" to categorize a patient's fall risk, however, these tools are primarily studied within in-patient units. The emergency department (ED) presents a unique environment with a distinct patient population and demographic. The Memorial Emergency Department Fall Risk Assessment Tool (MEDFRAT) has shown to be effective with predicting a patient's fall risk in the ED. This IRB-approved study aims to assess the predictive validity of the MEDFRAT by evaluating the sensitivity and specificity for predicting a patient's fall risk in an emergency department at a level 1 trauma center. METHODS: A retrospective cohort analysis was conducted using an electronic medical record (EMR) for patients who met study inclusion criteria at a level 1 trauma center ED. Extracted data includes MEDFRAT components, demographic information, and data from the Moving Safely Risk Assessment (MSRA) Tool, our institution's current fall assessment tool. A receiver operating characteristic (ROC) curve was constructed to determine the best cutoff for identifying any fall risk. Sensitivity, specificity, accuracy, positive likelihood ratio (LR+) and negative LR (LR-), with 95% CIs were then calculated for the cutoff value determined from the ROC curve. To compare overall tool performance, the areas under the ROC curves (AUC) were determined and compared with a z-test. RESULTS: The MEDFRAT had a significantly higher sensitivity compared to the MSRA (83.1% vs. 66.1%, p = 0.002), while the MSRA had a significantly higher specificity (84.5% vs. 69.0%, p = 0.012). For identifying any level of fall risk, ROC curve analysis showed that the cutoff providing the best trade-off between sensitivity and specificity for the MEDFRAT was a score of ≥1. Additionally, area under the curve was determined for the MEDFRAT and MSRA (0.817 vs. 0.737). CONCLUSION: This study confirms the validity of the MEDFRAT as an acceptable tool to predict in-hospital falls in a level 1 trauma center ED. Accurate identification of patients at a high risk of falling is critical for decreasing healthcare costs and improving health outcomes and patient safety.

Translation, validity and reliability of the fall risk scale for older adults.

INTRODUCTION: Falls in older adults are a common and serious threat to health and functional independence. It can cause psychological distress, inability to participate in activities of daily living, brain injury, fractures, and even death. The aim was to analyze the psychometric properties of the self-assessed fall risk scale (FRS) that measures the risk of falls in older adults in a central region of Chile, as well as to verify the concurrent validity against functional fitness tests. MATERIALS AND METHODS: A descriptive cross-sectional study was carried out in 222 older adults (OA) [34 males and 188 females] with an age range of 65 to 85 years. The 13-item self-perceived fall risk scale (FRS) was validated. Anthropometric measures (weight, height and waist circumference) were assessed. Five functional fitness tests were measured (right and left hand grip strength, biceps curl, up-and-go, agility and 6-minute walk test). Validation was performed by construct validation [(exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)] and concurrent validity. RESULTS: The EFA revealed 4 factors in the FRS scale [1: fear of falling (variance 27.1%), 2: use of assistive devices (variance 10.6%), 3: loss of sensation (variance 9.3%), and 4: limited mobility (variance 8.3%)]. Factor loadings ranged from ∼ 0.50 to 0.83 across the 4 components. The Kaiser-Meyer Olkin sample adequacy test (KMO) reflected adequate adequacy (KMO = 0.79, chi-square (X2) = 498.806, gl = 78, p = 0.00). The CFA showed a satisfactory final fit [chi-square (X2) = 126.748, Root mean squared error of approximation (RMSEA) = 0.042, Tucker-Lewis Index (TLI) = 0.946, Comparative fit index (CFI) = 0.935 y Normed fit index (NFI) = 0.90. The relationships between the FRS scale and functional fitness tests (right and left hand grip strength, biceps curl, up-and-go, agility and 6-minute walk test) ranged from low to moderate (r= -0.23 to 0.41). CONCLUSION: The FRS scale showed acceptable validity and reliability in older adults in central region of Chile. It is expected that this scale will be useful for assessing fall risk in clinical and epidemiological settings in the aging Chilean population.

The mediating effect of nutrition on oral frailty and fall risk in community-dwelling elderly people.

BACKGROUND: Population aging is accelerating, particularly in Asian countries. Falls are the leading cause of unintentional injuries in the elderly over 60 years old in China. Hence, it is crucial to anticipate the risk factors associated with fall risk. We aimed to explore whether oral frailty and fall risk were reciprocally related and whether nutrition mediated their association. METHODS: From October 2022 to March 2023, a total of 409 elderly individuals from the Yangzhou community were selected using the convenience sampling method. Cross-sectional data on older adults' oral frailty, nutrition, and fall risk were collected using questionnaires. Data analysis was performed using SPSS 27.0 and PROCESS macro. RESULTS: The fall risk score was 1.0 (ranging from 0 to 4.0), with 107 cases (26.2%) identified as being at risk of falling. Spearman correlation analysis revealed a positive correlation between oral frailty and the risk of falls (rs = 0.430, P < 0.01). Nutrition was found to have a negative correlation with both oral frailty and fall risk (rs=-0.519、-0.457, P < 0.01). When controlling for covariates, it was observed that nutrition mediated the relationship between oral frailty and falls. The mediating effect value accounted for 48.8% of the total effect (P < 0.01). CONCLUSIONS: Oral frailty was significantly associated with fall risk, and nutrition might be a mediating factor for adverse effects of oral frailty and fall risk. Enhancing the nutrition of older individuals is a vital approach to mitigating fall risk among those with oral frailty.

Fall risk factors among poly-medicated older Lebanese patients in primary care settings: a secondary cross-sectional analysis of the "MGPIDP-L project".

BACKGROUND: Falling is a major concern for the health of older adults and significantly affects their quality of life. Identifying the various risk factors and the differences between older patients can be challenging. The objective of this study was to identify the risk factors for falls among polymedicated community-dwelling older Lebanese patients following a medication review. METHODS: In this analytical cross-sectional study, we examined the risk factors for falls in 850 patients aged ≥ 65 years who were taking ≥ 5 medications daily. The study involved conducting a medication review over the course of a year in primary care settings and using multivariate logistic regression analysis to analyze the data. RESULTS: Our results showed that 106 (19.5%) of the 850 included patients had fallen at least once in the three months prior to the medication review. Loss of appetite and functional dependence were identified as the most significant predictors of falls ORa = 3.020, CI [2.074-4.397] and ORa = 2.877, CI [1.787-4.632], respectively. Other risk factors for falls included drowsiness ORa = 2.172, CI [1.499-3.145], and the use of beta-blockers ORa = 1.943, CI [1.339-2.820]. CONCLUSION: Our study highlights the importance of addressing multiple risk factors for falls among Lebanese older adults and emphasizes the need for customized interventions and ongoing monitoring to prevent falls and improve health outcomes. This study sheds light on a critical issue in the Lebanese older population and provides valuable insight into the complex nature of falls among poly-medicated Lebanese community-dwelling older adults. TRIAL REGISTRATION: 2021REC-001- INSPECT -09-04.

Identifying sensors-based parameters associated with fall risk in community-dwelling older adults: an investigation and interpretation of discriminatory parameters.

BACKGROUND: Falls 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. METHODS: Forty-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. RESULTS: Fifteen 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. CONCLUSIONS: Utilizing 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.

Medication-based profiling of older orthopedic patients: a multicenter cross-sectional study.

BACKGROUND: Managing medication use in older orthopedic patients is imperative to extend their healthy life expectancy in an aging society. However, the actual situation regarding polypharmacy, the intake of potentially inappropriate medications (PIMs), and fall risk-increasing drugs (FRIDs) among older orthopedic patients is not well characterized. This study aimed to investigate the medication-based profiles of older orthopedic patients to highlight the critical points of concern. METHODS: We retrospectively reviewed the clinical data of consecutive patients aged ≥ 65 years who underwent orthopedic surgery at two acute care hospitals between April 2020 and March 2021. The cutoff number of prescribed drugs for polypharmacy was set at 6. According to the specified guidelines, 19 categories of drugs were identified as PIMs, and 10 categories were classified as FRIDs. RESULTS: A total of 995 older patients with orthopedic surgery were assessed, of which 57.4% were diagnosed with polypharmacy, 66.0% were receiving PIMs, and 41.7% were receiving FRIDs. The prevalence of FRID intake did not significantly differ among patients with degenerative spinal disease (n = 316), degenerative disease of extremities (n = 331), and fractures (n = 272). Compared with patients with degenerative disease of the extremities, the multivariable-adjusted prevalence ratios (PRs) of polypharmacy and PIM intake were significantly higher in patients with degenerative spinal disease (1.26 [confidence intervals (CI): 1.11-1.44] and 1.12 [CI: 1.00-1.25]), respectively. Use of antiemetic drugs (adjusted PR, 13.36; 95% CI: 3.14-56.81) and nonsteroidal anti-inflammatory drugs (adjusted PR, 1.37; 95% CI: 1.05-1.78) was significantly higher in patients with degenerative spinal disease. Among patients with degenerative spinal disease, the prevalence of antiemetic drug intake was 8.7% in lumbar spinal patients and 0% in cervical spinal patients. CONCLUSIONS: More than half of the orthopedic patients in this study were affected by polypharmacy, and approximately two-thirds were prescribed some form of PIMs. Patients with degenerative spinal disease showed a significantly higher prevalence of polypharmacy and PIM use compared with other orthopedic diseases. Particular attention should be paid to the high frequency of antiemetic drugs and nonsteroidal anti-inflammatory drugs intake among patients with degenerative lumbar spine conditions.

The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review.

BACKGROUND: Falls and their consequences are a serious public health problem worldwide. Each year, 37.3 million falls requiring medical attention occur. Therefore, the analysis of fall risk is of great importance for prevention. Artificial intelligence (AI) represents an innovative tool for creating predictive statistical models of fall risk through data analysis. OBJECTIVE: The aim of this review was to analyze the available evidence on the applications of AI in the analysis of data related to postural control and fall risk. METHODS: A literature search was conducted in 6 databases with the following inclusion criteria: the articles had to be published within the last 5 years (from 2018 to 2024), they had to apply some method of AI, AI analyses had to be applied to data from samples consisting of humans, and the analyzed sample had to consist of individuals with independent walking with or without the assistance of external orthopedic devices. RESULTS: We obtained a total of 3858 articles, of which 22 were finally selected. Data extraction for subsequent analysis varied in the different studies: 82% (18/22) of them extracted data through tests or functional assessments, and the remaining 18% (4/22) of them extracted through existing medical records. Different AI techniques were used throughout the articles. All the research included in the review obtained accuracy values of >70% in the predictive models obtained through AI. CONCLUSIONS: The use of AI proves to be a valuable tool for creating predictive models of fall risk. The use of this tool could have a significant socioeconomic impact as it enables the development of low-cost predictive models with a high level of accuracy. TRIAL REGISTRATION: PROSPERO CRD42023443277; https://tinyurl.com/4sb72ssv.

Enhancing Patient Safety Through an Integrated Internet of Things Patient Care System: Large Quasi-Experimental Study on Fall Prevention.

BACKGROUND: The challenge of preventing in-patient falls remains one of the most critical concerns in health care. OBJECTIVE: This study aims to investigate the effect of an integrated Internet of Things (IoT) smart patient care system on fall prevention. METHODS: A quasi-experimental study design is used. The smart patient care system is an integrated IoT system combining a motion-sensing mattress for bed-exit detection, specifying different types of patient calls, integrating a health care staff scheduling system, and allowing health care staff to receive and respond to alarms via mobile devices. Unadjusted and adjusted logistic regression models were used to investigate the relationship between the use of the IoT system and bedside falls compared with a traditional patient care system. RESULTS: In total, 1300 patients were recruited from a medical center in Taiwan. The IoT patient care system detected an average of 13.5 potential falls per day without any false alarms, whereas the traditional system issued about 11 bed-exit alarms daily, with approximately 4 being false, effectively identifying 7 potential falls. The bedside fall incidence during hospitalization was 1.2% (n=8) in the traditional patient care system ward and 0.1% (n=1) in the smart ward. We found that the likelihood of bedside falls in wards with the IoT system was reduced by 88% (odds ratio 0.12, 95% CI 0.01-0.97; P=.047). CONCLUSIONS: The integrated IoT smart patient care system might prevent falls by assisting health care staff with efficient and resilient responses to bed-exit detection. Future product development and research are recommended to introduce IoT into patient care systems combining bed-exit alerts to prevent inpatient falls and address challenges in patient safety.

Congruency and its related factors between patients' fall risk perception and nurses' fall risk assessment in acute care hospitals.

INTRODUCTION: Inpatients need to recognize their fall risk accurately and objectively. Nurses need to assess how patients perceive their fall risk and identify the factors that influence patients' fall risk perception. PURPOSE: This study aims to explore the congruency between nurses' fall risk assessment and patients' perception of fall risk and identify factors related to the non-congruency of fall risk. DESIGNS: A descriptive and cross-sectional design was used. The study enrolled 386 patients who were admitted to an acute care hospital. Six nurses assessed the participants' fall risk. Congruency was classified using the Morse Fall Scale for nurses and the Fall Risk Perception Questionnaire for patients. FINDINGS: The nurses' fall risk assessments and patients' fall risk perceptions were congruent in 57% of the participants. Underestimation of the patient's risk of falling was associated with gender (women), long hospitalization period, department (orthopedics), low fall efficacy, and history of falls before hospitalization. Overestimation of fall risk was associated with age group, gender (men), department, and a high health literacy score. In the multiple logistic regression, the factors related to the underestimation of fall risk were hospitalization period and department, and the factors related to the overestimation of fall risk were health literacy and department. CONCLUSIONS: Nurses should consider the patient's perception of fall risk and incorporate it into fall prevention interventions. CLINICAL RELEVANCE: Nurses need to evaluate whether patients perceive the risk of falling consistently. For patients who underestimate or overestimate their fall risk, it may be helpful to consider clinical and fall-related characteristics together when evaluating their perception of fall risk.

Enhancing fall risk assessment: instrumenting vision with deep learning during walks.

BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait. METHOD: The approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset. RESULTS: VARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications. CONCLUSION: The instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common.

Physical Functioning, Physical Activity, and Variability in Gait Performance during the Six-Minute Walk Test.

Instrumenting the six-minute walk test (6MWT) adds information about gait quality and insight into fall risk. Being physically active and preserving multi-directional stepping abilities are also important for fall risk reduction. This analysis investigated the relationship of gait quality during the 6MWT with physical functioning and physical activity. Twenty-one veterans (62.2 ± 6.4 years) completed the four square step test (FSST) multi-directional stepping assessment, a gait speed assessment, health questionnaires, and the accelerometer-instrumented 6MWT. An activity monitor worn at home captured free-living physical activity. Gait measures were not significantly different between minutes of the 6MWT. However, participants with greater increases in stride time (ρ = -0.594, p < 0.01) and stance time (ρ = -0.679, p < 0.01) during the 6MWT reported lower physical functioning. Neither physical activity nor sedentary time were related to 6MWT gait quality. Participants exploring a larger range in stride time variability (ρ = 0.614, p < 0.01) and stance time variability (ρ = 0.498, p < 0.05) during the 6MWT required more time to complete the FSST. Participants needing at least 15 s to complete the FSST meaningfully differed from those completing the FSST more quickly on all gait measures studied. Instrumenting the 6MWT helps detect ranges of gait performance and provides insight into functional limitations missed with uninstrumented administration. Established FSST cut points identify aging adults with poorer gait quality.

A Computer Vision-Based System to Help Health Professionals to Apply Tests for Fall Risk Assessment.

The increase in life expectancy, and the consequent growth of the elderly population, represents a major challenge to guarantee adequate health and social care. The proposed system aims to provide a tool that automates the evaluation of gait and balance, essential to prevent falls in older people. Through an RGB-D camera, it is possible to capture and digitally represent certain parameters that describe how users carry out certain human motions and poses. Such individual motions and poses are actually related to items included in many well-known gait and balance evaluation tests. According to that information, therapists, who would not need to be present during the execution of the exercises, evaluate the results of such tests and could issue a diagnosis by storing and analyzing the sequences provided by the developed system. The system was validated in a laboratory scenario, and subsequently a trial was carried out in a nursing home with six residents. Results demonstrate the usefulness of the proposed system and the ease of objectively evaluating the main items of clinical tests by using the parameters calculated from information acquired with the RGB-D sensor. In addition, it lays the future foundations for creating a Cloud-based platform for remote fall risk assessment and its integration with a mobile assistant robot, and for designing Artificial Intelligence models that can detect patterns and identify pathologies for enabling therapists to prevent falls in users under risk.

Baseline Measures of Physical Activity and Function Do Not Predict Future Fall Incidence in Sedentary Older Adults: A Prospective Cohort Study.

Physical activity (PA) and physical function (PF) are modifiable risk factors for falls in older adults, but their ability to predict future fall incidence is unclear. The purpose of this study was to determine the predictive ability of baseline measures of PA, PF, and lower limb strength on future falls. A total of 104 participants underwent baseline assessments of PA, PF, and lower limb strength. Falls were monitored prospectively for 12 months. Eighteen participants fell at least once during the 12-month follow-up. Participants recorded almost exclusively sedentary levels of activity. PA, PF, and lower limb strength did not differ between fallers and nonfallers. Twelve participants, who reported a minor musculoskeletal injury in the past 6 months, experienced a fall. The results of this study suggest that in a cohort of highly functioning, sedentary older adults, PA does not distinguish fallers from nonfallers and that the presence of a recent musculoskeletal injury appears to be a possible risk factor for falling.

Relationship Between Executive Function Subdomains and Postural Balance in Community-Dwelling Older Adults.

BACKGROUND: Executive function (EF) deficits are a significant risk factor for falls among older adults (OAs). However, relationship between EF subdomains (shifting, updating, and inhibition), postural balance (PB), and fall risk in healthy OAs, remains poorly understood. OBJECTIVE: This study aimed to investigate the relationship between EF subdomains (shifting, updating, and inhibition) and PB, and to assess their impact on risk of falls in community-dwelling OAs. METHODS: A cross-sectional study involving 50 OAs aged over 60 years (average age of 72 years) was conducted. Participants underwent assessments of EF subdomains and PB using validated tests. A correlation analysis was employed to examine the relationships between EF and PB. RESULTS: The study revealed significant correlations between subdomains and PB. Mental set shifting (r = -.539; p < .001) and inhibition (r = -.395; p = .050) exhibited inverse relationships with PB. Stepwise multiple linear regression showed that Trail Making Test Part B was associated with the PB (R2 = .42, p < .001). CONCLUSION: These findings highlight the importance of assessing EF subdomains, particularly shifting and inhibition, to identify risk of falls. Trail Making Test Part B largely explains the variability of the PB. Integrating PB assessments and EF training, such as the Mini-BESTest, into routine care can be vital for fall prevention strategies. Significance/Implications: This knowledge underscores the need for cognitive training interventions focusing on shifting and inhibition to enhance PB and potentially reduce falls. Additionally, incorporation of EF assessment tools as Trail Making Test Part B and the Mini-BESTest into routine clinical practice for community-dwelling OAs is recommended to address fall prevention strategies.