Fall Risk Groups Research Articles

Cognitive and Motor Cortical Activity During Cognitively Demanding Stepping Tasks in Older People at Low and High Risk of Falling.

Background: Choice stepping reaction time tasks are underpinned by neuropsychological, sensorimotor, and balance systems and therefore offer good indices of fall risk and physical and cognitive frailty. However, little is known of the neural mechanisms for impaired stepping and associated fall risk in older people. We investigated cognitive and motor cortical activity during cognitively demanding stepping reaction time tasks using functional near-infrared spectroscopy (fNIRS) in older people at low and high fall risk.Methods: Ninety-five older adults [mean (SD) 71.4 (4.9) years, 23 men] were categorized as low or high fall risk [based on 12-month fall history (≥2 falls) and/or Physiological Profile Assessment fall risk score ≥1]. Participants performed a choice stepping reaction time test and a more cognitively demanding Stroop stepping task on a computerized step mat. Cortical activity in cognitive [dorsolateral prefrontal cortex (DLPFC)] and motor (supplementary motor area and premotor cortex) regions was recorded using fNIRS. Stepping performance and cortical activity were contrasted between the groups and between the choice and Stroop stepping conditions.Results: Compared with the low fall risk group (n = 71), the high fall risk group (n = 24) exhibited significantly greater DLPFC activity and increased intra-individual variability in stepping response time during the Stroop stepping task. The high fall risk group DLPFC activity was greater during the performance of Stroop stepping task in comparison with choice stepping reaction time. Regardless of group, the Stroop stepping task elicited increased cortical activity in the supplementary motor area and premotor cortex together with increased mean and intra-individual variability of stepping response times.Conclusions: Older people at high fall risk exhibited increased DLPFC activity and stepping response time variability when completing a cognitively demanding stepping test compared with those at low fall risk and to a simpler choice-stepping reaction time test. This increased hemodynamic response might comprise a compensatory process for postural control deficits and/or reflect a degree of DLPFC neural inefficiency in people with increased fall risk.

Classification of fall directions via wearable motion sensors

Effective fall-detection and classification systems are vital in mitigating severe medical and economical consequences of falls to people in the fall risk groups. One class of such systems is based on wearable sensors. While there is a vast amount of academic work on this class of systems, not much effort has been devoted to the investigation of effective and robust algorithms and like-for-like comparison of state-of-the-art algorithms using a sufficiently large dataset. In this article, fall-direction classification algorithms are presented and compared on an extensive dataset, comprising a total of 1600 fall trials. Eight machine learning classifiers are implemented for fall-direction classification into four basic directions (forward, backward, right, and left). These are, namely, Bayesian decision making (BDM), least squares method (LSM), k-nearest neighbor classifier (k-NN), artificial neural networks (ANNs), support vector machines (SVMs), decision-tree classifier (DTC), random forest (RF), and adaptive boosting or AdaBoost (AB). BDM achieves perfect classification, followed by k-NN, SVM, and RF. Data acquired from only a single motion sensor unit, worn at the waist of the subject, are processed for experimental verification. Four of the classifiers (BDM, LSM, k-NN, and ANN) are modified to handle the presence of data from an unknown class and evaluated on the same dataset. In this robustness analysis, ANN and k-NN yield accuracies above 96.2%. The results obtained in this study are promising in developing real-world fall-classification systems as they enable fast and reliable classification of fall directions.

The serum 25(OH)D level and hand grip strength for fall risk assessment among osteoporotic elderly Japanese women

SummaryWe investigated the relationship between serum 25(OH)D levels, grip strength, and fall score in elderly osteoporotic women for fall risk assessment. Both low serum 25(OH)D and low grip strength were independently associated with increased fall risk. The serum 25(OH)D cutoff specific to increased fall risk was 14 mg/dL (35 nmol/L).PurposeThis study aimed to establish a cutoff value of serum 25-hydroxyvitamin D (25(OH)D) for fall assessment and investigate the relationship between serum 25(OH)D, grip strength, and fall score adjusted for age in osteoporotic elderly Japanese women.MethodsThis is a cross-sectional study utilizing collected data of osteoporotic elderly (age ≥65 years) female patients. A questionnaire for fall risk assessment was used, in which a score ≥ 6 was determined as increased fall risk. Serum 25(OH)D levels and grip strength were measured, and the cutoff points were calculated by receiver operating curve (ROC) analysis. Logistic regression analysis with age adjustment was conducted for potential risk factors for fall.ResultsAfter applying eligibility criteria, finally, 349 patients were enrolled. The median patient age was 77.0 years, and the mean serum 25(OH)D level was 15.6 ng/mL (36 nmol/L). Based on the ROC analysis, we defined the cutoff values of serum 25(OH)D level and grip strength as 14 ng/mL (35 nmol/L) and 15 kg, respectively. A multivariate analysis adjusted for age was conducted. Low serum 25(OH)D level and grip strength were independent risk factors for ≥6 fall risk scores.ConclusionBoth low serum 25(OH)D level and low grip strength were independently associated with increased fall risk score in osteoporotic elderly women. The appropriate serum 25(OH)D cutoff specific to the increased fall risk group in this population was 14 mg/dL (35 nmol/L). These findings might be used for the identification of patients with high fall risks. These results should be confirmed in other patient groups.

Multisensory integration involved in the body perception of community-dwelling older adults

This study investigates how the multisensory integration in body perception changes with increasing age, and whether it is associated with older adults’ risk of falling. For this, the rubber hand illusion (RHI) and rubber foot illusion (RFI) were used. Twenty-eight community-dwelling older adults and 25 university students were recruited. They viewed a rubber hand or foot that was stimulated in synchrony or asynchrony with their own hidden hand or foot. The illusion was assessed by using a questionnaire, and measuring the proprioceptive drift and latency. The Timed Up and Go Test was used to classify the older adults into lower and higher fall-risk groups. No difference was observed in the RHI between the younger and older adults. However, several differences were observed in the RFI. Specifically, the older adults with a lower fall-risk hardly experienced the illusion, whereas those with a higher fall-risk experienced it with a shorter latency and no weaker than the younger adults. These results suggest that in older adults, the mechanism of multisensory integration for constructing body perception can change depending on the stimulated body parts, and that the risk of falling is associated with multisensory integration.

Detection of Generalized Tonic Clonic Seizures and Falls in Unconstraint Environment Using Smartphone Accelerometer

The detection of Generalized Tonic Clonic Seizures (GTCS) and Falls is of utmost importance due to the increase in prevalence of epilepsy and Sudden Death in Epileptic Patients during CoVID-19 pandemic, and prevention of serious injuries in Fall risk groups such as elderly requiring continuous monitoring for disease management and assisted living etc. Monitoring of Activities of Daily Living (ADLs) can assist in the detection of symptoms and onset of neurological disorders such as Alzheimer’s, stroke, and epileptic seizures. With a host of embedded sensors, improved memory, enhanced processing capabilities and availability to masses, smartphones can be used for Human Activity Recognition (HAR) through continuous monitoring of ADLs. This paper presents a tri-axial accelerometer-based approach to detect and classify activities performed by individuals by applying machine learning algorithms including RF, J48, NB, LMT and SVM to movement data. Movement data is collected in real-time from the embedded accelerometer of a smartphone worn by individual on upper-left arm in unconstraint environment. It is pre-processed using time and frequency domain analysis and spatial domain features are computed. Supervised machine learning techniques are applied to classify ADLs into five classes based on the intensity of movements: Stationary, Light Ambulatory, Intense Ambulatory, GTCS and Falls. We also used training data from MyNeuroHealth dataset collected from 23 individuals including epilepsy patients. Based on gathered results, Random Forest outperforms other classifiers with classification accuracy of 99.6% for stationary, 81.5% for light ambulatory, 99.8% for intense ambulatory and GTCS, and 97.2% for Falls corresponding to training data of 14000 samples. To date, activity classification in our system has been implemented on cloud instead of mobile phone application as subjects are using smartphones with dissimilar software and hardware specifications for assisted living applications.

Appling Decision Tree Technique To Predict Fall Risks Classified By Functional Fitness In Older Adults

PURPOSE: To examine an accuracy of the fall risk classification predicted by senior functional fitness tests and health conditions in Korean older adults utilizing a decision tree technique, which is a machine learning algorithm METHODS: A total of 732 older adults (Males 45.9%, age: 73.51±6.20yrs, BMI: 24.07) participated in Korea Survey of National Physical Fitness (KSNPF). All participants performed the senior physical fitness test (SPFT) including body composition (FAT%), 6min walk, hand grip(HG), timed up-and-go (TUG), and chair sit-and-stand. Also, demographic variables (income, employment, etc.) and health markers were measured, which were including blood pressure & waist and hip circumferences as well as physical activity levels and health conditions (disease, medication, and fall experiences). All utilized measures were validated for the Korean elderly in 2014. To determine a classifier of a fall risk and to set cut-off scores of the fall risk classification, a decision tree technique with CHAID algorithm (Kass, 1980) was applied. To examine the accuracy of the fall risk classification predicted by selected variables, 80% of participants were randomly selected to derive the equation for a training group (GR) and the others were assigned for a cross-validation GR (20% for testing). RESULTS: Only TUG and HG were significant classifiers with 87.6% of accuracy in the testing GR and 86.6% of precision in the cross-validation GR, respectively. The cut-off score of TUG was 7.13sec. (chi-square=21.22, p<.001), in which 21.1% of participants were classified into the fall risk GR. Within the TUG GR (<7.13sec.), the cut-off score of HG were set as 23.6kg (chi-square=14.87, p<.001), and 52.8% (<23.6kg) was classified into the fall risk GR. CONCLUSIONS: Among SPFT tests and health related variables, TUG and HG were relatively important to predict the fall risk for the healthy elderly in Korea. Coordination and strength exercise are critical for fall prevention in older adults. *Corresponding author ([email protected])

Relationship between postural stability and fall risk in elderly people with lumbar spondylosis during local vibratory stimulation for proprioception: a retrospective study

Purpose: Reduced proprioception affects fall risks in elderly people with lumbar spondylosis. The decrease in proprioception in the trunk or lower legs may contribute to a decline in postural stability. We aimed to investigate the association between proprioceptive postural stability and fall risks in elderly individuals with lumbar spondylosis.Materials and Methods: In this retrospective study, the centre-of-pressure displacement was determined in elderly individuals with lumbar spondylosis during upright stance while standing on a Wii Balance Board with their eyes closed (fall-risk group, n = 55; non-fall-risk group, n = 60). Vibratory stimulations at 30 Hz were applied to the lumbar multifidus and gastrocnemius to evaluate the relative contributions of proprioceptive signals used in postural control (relative proprioceptive weighting ratio).Results: Compared with the non-fall-risk group, the fall-risk group displayed a high relative proprioceptive weighting ratio (p = 0.024). Relative proprioceptive weighting ratio (odds ratio, 1.1; 95% confidence interval: 1.004–1.109) was independently associated with fall risks after adjusting for confounding factors. Among variables related to fall risk, the relative proprioceptive weighting ratio was a significant factor (p < 0.035).Conclusion: The fall-risk group of elderly individuals with lumbar spondylosis was dependent on the ankle strategy. The fall risk in elderly people with lumbar spondylosis could be due to over-dependence on the input from muscle spindles in the gastrocnemius.

Performance and Clinimetric Properties of the Timed Up From Floor Test Completed by Apparently Healthy Community-Dwelling Older Women.

Standing up from the floor is a demanding mobility activity with important implications. The purpose of this study was to describe performance and the clinimetric properties of the Timed Up From Floor (TUFF) test completed by apparently healthy community-dwelling older women. In this observational and methodological quality study, 52 community-dwelling women, 55 years and older, were examined. Convergent and discriminant validities were examined by analyzing the correlations of TUFF test times with other mobility variables and emotional status, respectively. Validity was further examined by comparing TUFF times between age groups and fall risk groups. Interrater reliability of the TUFF test was established by comparing the times obtained by 3 raters observing the same videotaped performances. Test-retest reliability was determined by having the same 3 raters observe videos of the same participants performing the TUFF test during a second session 1 week later. The grand mean (SD) TUFF time measured by all testers on the first day was 5.8 (2.9) seconds. Convergent validity was demonstrated by significant negative (P < .001) Spearman correlations between the TUFF test and the Physical Functioning Scale of the 36-Item Short Form Health Survey (SF-36) (-0.69), usual gait speed (-0.48), fast gait speed (-0.74), and the 30-second sit-to-stand test (-0.46). Discriminant validity was indicated by a low and nonsignificant correlation (0.17) between the TUFF test and the SF-36 Emotional Well-being Scale. Known-groups validity was supported by a significant difference in the TUFF test times of 2 age groups (P = .02) and 2 fall risk groups (P < .001). The TUFF test was determined to have excellent relative interrater reliability (intraclass correlation coefficient [ICC] of 0.99) and absolute reliability (minimal detectable change [MDC95%] of 0.8 seconds). Relative test-retest reliability was excellent with ICCs of 0.88 to 0.92. Corresponding MDC95% values were large (2.4-2.8 seconds and 40.7%-45.9%). The TUFF test is an informative, reliable, and valid tool suitable for documenting mobility limitations in independent community-dwelling older women. More information regarding responsiveness is required.

Relationship Between L4/5 Lumbar Multifidus Cross-Sectional Area Ratio and Fall Risk in Older Adults with Lumbar Spinal Stenosis: A Retrospective Study.

Various factors, including spinal deformities and trunk muscle atrophy, greatly affect the fall risk among older adults with lumbar spinal stenosis (LSS). However, the etiology of falls in older adults with degenerative LSS and trunk muscle atrophy is poorly understood. We investigated the association between trunk muscle atrophy and falls in older LSS patients. This retrospective study included 99 hospitalized older adults with LSS. Participants completed self-reported fall score questionnaires and were divided into the fall risk (n = 30) and non-fall risk (n = 69) groups. The patients’ low back pain visual analog scale score, Geriatric Depression Scale score, sagittal vertical axis, L4/5 lumbar multifidus cross-sectional area ratio (LMCSAR), and center of pressure (COP) values during quiet standing were evaluated. The fall risk group had a lower L4/5 LMCSAR (p = 0.002) and increased COP excursion (p = 0.034) than the non-fall risk group. No significant differences were observed in the other measured variables between the two groups. The L4/5 LMCSAR (p < 0.001) and COP (p = 0.024) were related to fall risk and may be useful in fall risk assessment in such populations. Strategies aimed at enhancing controlled lumbar segmental motion and improving trunk muscle stability or mass may decrease the fall risk in this cohort.

Abstract TP166: The Six Minute Walk Test as a Predictor for Fall Risk in Persons With Stroke

Introduction: Persons with stroke have increased risk for recurrent stroke, other chronic health conditions and falls. One option to reduce the risk of worsening health conditions is to increase physical activity by engaging in group medical fitness programs like cardiac rehabilitation (CR). CR programs utilize clinical measures for functional capacity, commonly exercise stress testing or the six-minute-walk test (6MWT). Absent is measurement and focus on balance or balance confidence. Supervising staff may be unaware of fall risk which is an important safety factor for persons with stroke. The purpose of this study was to determine the degree to which the 6MWT is associated with fall risk in community-dwelling persons with stroke. Methods: A cross-sectional analysis measured association between the 6MWT and fall risk in 66 persons with stroke. Fall risk is defined as a score on the Activities Balance Confidence Scale (ABC) of &lt; 81.1 based on a study by Beninato et al. (2009) which found significant accuracy of fall prediction with this cutoff (Sensitivity = 1.00, Specificity = 0.72(0.51-0.93)). The 6MWT and the 6MWT combined with other data differing between fall risk groups (e.g. walking speed, Berg Balance Scale and time since stroke) were evaluated using univariate logistic regression to determine influence on fall risk. The best fit model was used in Receiver Operating Characteristic (ROC) analysis to determine the area under the curve (AUC) to detect an increased risk of falls. Likelihood ratios and post-test probabilities were calculated. Results: The 6MWT was associated with fall risk in logistic regression (p=0.002) with an odds ratio (OR) of 0.995 (0.991,0.999), p=0.007). The AUC for the univariate 6MWT ROC model (best fit) was 0.701 (p=0.006). The cutoff for increased fall risk was 6MWT &lt; 331.65 meters. The post-test probability of fall risk was 74.3%, increased from a pre-test probability of 59.1%. Conclusion: The association between fall risk and 6MWT suggests that in addition to aerobic capacity and motor components, the 6MWT includes a fall risk/balance confidence component. In conclusion, utilizing the 6MWT to screen fall risk in CR and other community exercise programs can enhance safety for persons with stroke without additional testing burden.

Rehabilitation Services Use of Older Adults According to Fall-Risk Screening Guidelines.

To characterize rehabilitation services use of older adults according to fall-risk classification based on screening guidelines. Cross-sectional analysis of 2015 National Health and Aging Trends Study. Study participants' homes. National sample of 7,440 community-dwelling Medicare beneficiaries. In-person interviews and functional assessments. Based on Centers for Disease Control and Prevention Stopping Elderly Accidents, Deaths and Injuries criteria, participants were classified as low, moderate, or high fall risk. Twenty-three percent of older adults classified as moderate fall-risk (n = 2602) and 40.6% of those at high fall-risk (n = 940) reported rehabilitation services use in the past year. Among older adults who reported rehabilitation services in the past year (n = 1,505), treatment to address falls was reported by 2.8%, 12.6%, and 34.7% of those classified with low, moderate, and high fall-risk, respectively (p < 0.001). Older adults with high fall-risk who did not receive rehabilitation services had significantly better self-reported physical capacity (p = 0.02) but comparable physical performance (all p's > 0.05) relative to those who received rehabilitation. Older adults at high risk for falls were significantly more likely to report rehabilitation services use compared to those with low and moderate risk of falling. The findings also indicate that there is low adherence to national clinical recommendations for rehabilitation services use in older adults vulnerable to falls-related injury. Among the high fall-risk group, those who did not receive rehabilitation services had similarly low physical function as compared with those who received rehabilitation, indicating potential unmet need to address physical impairments related to fall-risk. J Am Geriatr Soc 67:100-107, 2019.

Association of fall history with the Timed Up and Go test score and the dual task cost: A cross-sectional study among independent community-dwelling older adults.

To investigate the associations between fall history and the Timed Up and Go (TUG) test (single-TUG test), TUG test while counting aloud backwards from 100 (dual-TUG test) and the dual-task cost (DTC) among independent community-dwelling older adults. This cross-sectional study included 537 older adults who lived independently in the community. Data on fall history in the previous year were obtained by self-administrated questionnaire. The single- and dual-TUG tests were carried out, and the DTC value was computed from these results. Associations between fall history and these TUG-related values were analyzed using multivariate logistic regression models. The participants were divided into fall risk groups using the cut-off values of those significantly associated with falling, and the odds ratios (OR) were computed. Slower single-TUG test scores and lower DTC values were significantly associated with fall history after adjusting for potential confounders (single-TUG test score: OR 1.133, 95% CI 1.029-1.249; DTC value: OR 0.984, 95% CI 0.968-0.998). Older adults with slower single-TUG test scores and lower DTC values reported a fall history more often than those in other categories (OR compared with the lower-risk single-TUG and lower-risk DTC groups: 3.474, 95% CI 1.881-6.570). Slower single-TUG test scores and lower DTC values are associated with fall history among independent community-dwelling older adults. To some extent, dual task performance might provide added value for fall assessment, compared with administering the TUG test alone. Geriatr Gerontol Int 2018; 18: 1189-1193.

The effects of a multicomponent intervention program on clinical outcomes associated with falls in healthy older adults.

Multicomponent intervention programs have been shown to be effective in reducing risk factors associated with falls, but the primary target population of these interventions is often low-functioning older adults. The purpose of this study was to investigate the effectiveness of a multicomponent intervention program focusing on balance and muscle strength for independently functioning community-dwelling older adults. Fifty-three independently functioning older adults, aged 80.09 ± 6.62 years, participated in a group exercise class (conducted 2 times/week for 8 weeks) emphasizing balance. Outcome measures were balance performance using the Fullerton Advanced Balance (FAB) scale and muscle strength using the Senior Fitness Test (SFT). The intervention improved balance (P < 0.001), and older adults who were classified as having high fall risks based on the FAB scores at pre-testing improved more than older adults who were classified as having low fall risks (P = 0.017). As a result, 22 participants transitioned from a high fall risk group at pre-testing to a low fall risk group at post-testing (P < 0.001). The intervention also enhanced both upper and lower muscle extremity strength based on SFT results (P < 0.001) regardless of participants' classification of fall risk status. The multicomponent intervention conducted two times per week for 8 weeks was effective in improving balance and enhancing muscle strength of independently functioning older adults. The results underscore the importance of providing fall prevention interventions to healthy older adults, a population often not a target of balance interventions.

Falls, Anticoagulation, and the Elderly: Are We Inappropriately Treating Atrial Fibrillation in this High-Risk Population?

There are approximately 2.3 million people with atrial fibrillation in the US. The incidence is rising as the elderly population expands. Anticoagulation is a critical decision because the incidence of stroke is increased 5-fold in patients with atrial fibrillation. From a geriatric trauma perspective, this creates a unique patient population, as 50% of people over the age of 80 years will fall at least once per year. A common concern for physicians dealing with geriatric trauma victims is whether anticoagulation is appropriate in this high fall-risk group. We performed a retrospective, comprehensive chart review of all patients admitted to a level I trauma center with atrial fibrillation, who fell while taking anticoagulation from May 2013 to April 2016. The patients were captured by the hospital trauma database. The CHA2DS2-VASc and HAS-BLED scores were calculated for each patient. Statistical analysis of the demographics, comorbidities, and severity of injuries was completed. A total of 242 patients were identified. Fifty-eight percent of the patient population was female, and average age was 78 years old. The average CHA2DS2-VASc and HAS-BLED scores were 5.25 and 3.05, respectively. We identified a 1.6% incidence of CHA2DS2-VASc equal to 0 or 1. Overall mortality was 32% at the time of review. Of the patient population, 8.6% were deceased within 30 days of the fall. There is a very low incidence of inappropriate anticoagulation for atrial fibrillation. After a fall, the risk of morbidity and mortality is very high. The mortality rate is independent of age and comorbidities.

Lower Physical Activity in Persons with Multiple Sclerosis at Increased Fall Risk: A Cross-sectional Study.

Persons with multiple sclerosis (MS) often report being afraid of falling, and this may have effects on physical activity (PA) engagement. This study investigated PA levels in persons with MS as a function of fall risk categories. Forty-seven persons with MS participated in the study and were categorized into either increased fall risk (IFR; n = 21; 55.5 ± 9.0 years) or normal fall risk (NFR; n = 26; 51.2 ± 12.9 years) groups based on scores from the Activities-Balance Confidence scale. PA was measured by accelerometer and expressed as average steps per day, and time spent in sedentary behavior, light PA, and moderate to vigorous physical activity over the course of 7 consecutive days. Univariate and covariate analyses were used to compare the differences in PA between fall risk groups. The average steps per day of the NFR group was significant higher compared with the IFR group (6024 ± 2533.1 vs. 2599 ± 1622.7 steps; P < 0.001), and the difference remained after controlling for disability level (5351 ± 2298.6 vs. 3432 ± 2363.6 steps; P = 0.016). There were no differences in light PA and moderate to vigorous physical activity between groups after controlling for disability level. Persons with MS at IFR accumulate fewer steps per day compared with those at NFR. This underscores the need for well-designed interventions targeting walking in this population who are far from the recommended 10,000 steps, particularly those with IFR.

Mobility measures differentiate falls risk status in persons with multiple sclerosis: An exploratory study.

Falls are of great concern among persons with multiple sclerosis (MS). To examine differences in metrics of mobility, postural control, and cognition in persons with MS with distinct fall risk status; and to investigate predictors of fall risk group membership using discriminant analysis. Forty-seven persons with MS completed the Activities-Balance Confidence (ABC) Scale and underwent a battery of assessments of mobility, balance, and cognition. Participants further wore an accelerometer for 7 days as an assessment of steps/day. Participants were allocated into fall risk groups based on ABC scale scores (increased fall risk (IFR); and normal fall risk (NFR)). We examined univariate differences between groups using ANOVA, and discriminant function analysis (DFA) identified the significant multivariate predictors of FR status. After controlling for disability level, the IFR group had significantly (p < 0.05) worse scores on measures of mobility (i.e., MSWS-12, 6 MW, and steps/day) compared to the NFR group. DFA identified MSWS-12 and 6 MW scores as significant (p < 0.05) predictors of fall risk group membership. Those two variables collectively explained 55% of variance in fall risk grouping. The findings suggest that mobility should be the focus of rehabilitation programs in persons with MS, especially for those at IFR.

Activity Monitoring and Heart Rate Variability as Indicators of Fall Risk: Proof-of-Concept for Application of Wearable Sensors in the Acute Care Setting.

Growing concern for falls in acute care settings could be addressed with objective evaluation of fall risk. The current proof-of-concept study evaluated the feasibility of using a chest-worn sensor during hospitalization to determine fall risk. Physical activity and heart rate variability (HRV) of 31 volunteers admitted to a 29-bed adult inpatient unit were recorded using a single chest-worn sensor. Sensor data during the first 24-hour recording were analyzed. Participants were stratified using the Hendrich II fall risk assessment into high and low fall risk groups. Univariate analysis revealed age, daytime activity, nighttime side lying posture, and HRV were significantly different between groups. Results suggest feasibility of wearable technology to consciously monitor physical activity, sleep postures, and HRV as potential markers of fall risk in the acute care setting. Further study is warranted to confirm the results and examine the efficacy of the proposed wearable technology to manage falls in hospitals. [Journal of Gerontological Nursing, 43(7), 53-62.].

Geriatric falls in the context of a hospital fall prevention program: delirium, low body mass index, and other risk factors.

BackgroundInpatient geriatric falls are a frequent complication of hospital care that results in significant morbidity and mortality.ObjectiveEvaluate factors associated with falls in geriatric inpatients after implementation of the fall prevention program.MethodsProspective observational study comprised of 788 consecutive patients aged 79.5±7.6 years ( ± standard deviation) (66% women and 34% men) admitted to the subacute geriatric ward. Comprehensive geriatric assessment (including Mini-Mental State Examination, Barthel Index of Activities of Daily Living, and modified Get-up and Go Test) was performed. Confusion Assessment Method was used for diagnosis of delirium. Patients were categorized into low, moderate, or high fall risk groups after clinical and functional assessment.ResultsAbout 15.9%, 21.1%, and 63.1% of participants were classified into low, moderate, and high fall risk groups, respectively. Twenty-seven falls were recorded in 26 patients. Increased fall probability was associated with age ≥76 years (P<0.001), body mass index (BMI) <23.5 (P=0.007), Mini-Mental State Examination <20 (P=0.004), Barthel Index <65 (P=0.002), hemoglobin <7.69 mmol/L (P=0.017), serum protein <70 g/L (P=0.008), albumin <32 g/L (P=0.001), and calcium level <2.27 mmol/L. Four independent factors associated with fall risk were included in the multivariate logistic regression model: delirium (odds ratio [OR] =7.33; 95% confidence interval [95% CI] =2.76–19.49; P<0.001), history of falls (OR =2.55; 95% CI =1.05–6.19; P=0.039), age (OR =1.14; 95% CI =1.05–1.23; P=0.001), and BMI (OR =0.91; 95% CI =0.83–0.99; P=0.034).ConclusionDelirium, history of falls, and advanced age seem to be the primary risk factors for geriatric falls in the context of a hospital fall prevention program. Higher BMI appears to be associated with protection against inpatient geriatric falls.

Problems and fall risk determinants of quality of life in older adults with increased risk of falling.

Determine quality of life and its association with fall risk factors in older adults with increased risk of falling. A total of 597 community-dwelling Taiwanese older adults who were screened to have increased risk of falling participated in the present study. The fall risk factors included sociodemographics, physical and psychological function, Timed Up and Go, past fall/medical histories, fear of falling and medications. The Euro QOL EQ-5D was used to measure health-related quality of life. Pain/discomfort was the EQ-5D dimension most frequently reported to be impaired (35%), regardless of the level of fall risk or age groups, followed by mobility (25%). Hierarchical regression analysis showed that Geriatric Depression Scale, Mini-Mental State Examination, physiological function, up-and-go, fear of falling and psychotropic medication were independent predictors for total EQ-5D, explaining 68.37% of the variance. Logistic regression analysis showed that for the five EQ-5D dimensions, Geriatric Depression Scale and Up and Go time were the most common determinants. Pain/discomfort was the leading impairment, and greater Geriatric Depression Scale and longer up-and-go time were the main contributing factors in declines in quality of life in older adults with increased risk of falling. These factors are often modifiable, and their management might be considered a priority in falls prevention.

Detecting falls with wearable sensors using machine learning techniques.

Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and magnetometer/compass). Fourteen volunteers perform a standardized set of movements including 20 voluntary falls and 16 activities of daily living (ADLs), resulting in a large dataset with 2520 trials. To reduce the computational complexity of training and testing the classifiers, we focus on the raw data for each sensor in a 4 s time window around the point of peak total acceleration of the waist sensor, and then perform feature extraction and reduction. Most earlier studies on fall detection employ rule-based approaches that rely on simple thresholding of the sensor outputs. We successfully distinguish falls from ADLs using six machine learning techniques (classifiers): the k-nearest neighbor (k-NN) classifier, least squares method (LSM), support vector machines (SVM), Bayesian decision making (BDM), dynamic time warping (DTW), and artificial neural networks (ANNs). We compare the performance and the computational complexity of the classifiers and achieve the best results with the k-NN classifier and LSM, with sensitivity, specificity, and accuracy all above 99%. These classifiers also have acceptable computational requirements for training and testing. Our approach would be applicable in real-world scenarios where data records of indeterminate length, containing multiple activities in sequence, are recorded.