Nienke M. Kosse

Sensor technologies aiming at fall prevention in institutionalized old adults: A synthesis of current knowledge

BACKGROUND Falls are a serious health problem in old adults especially in nursing home residents and hospitalized patients. To prevent elderly from falling, sensors have been increasingly used in intramural care settings. However, there is no clear overview of the current used technologies and their results in fall prevention. OBJECTIVES The present study reviews sensor systems that prevent falls in geriatric patients living in an intramural setting and describe fall rates, fall-related injuries, false alarms, and user experience associated with such systems. METHODS We conducted a systematic search for studies that used sensor technologies with the aim to prevent falls in institutionalized geriatric patients. RESULTS A total of 12 studies met the search criteria. Three randomized clinical trials reported no reductions in fall rate but three before-after studies reported significant reductions of 2.4-37 falls per 1000 patient days. Although there was up to 77% reduction in fall-related injuries and there was relatively low, 16%, rate of false alarms, the current data are inconsistent whether current sensor technologies are effective in reducing the number of falls in institutionalized geriatric patients. The occurrence of false alarms (16%) was too high to maintain full attention of the nursing staff. Additionally including the users opinion and demands in developing and introducing sensor systems into intramural care settings seems to be required to make an intervention successful. CONCLUSION The evidence is inconsistent whether the current sensor systems can prevent falls and fall-related injuries in institutionalized elderly. Further research should focus more comprehensively on user requirements and effective ways using intelligent alarms.

Factors related to the high fall rate in long-term care residents with dementia

BACKGROUND Falls in long-term care residents with dementia represent a costly but unresolved safety issue. The aim of the present study was to (1) determine the incidence of falls, fall-related injuries and fall circumstances, and (2) identify the relationship between patient characteristics and fall rate in long-term care residents with dementia. METHODS Twenty long-term care residents with dementia (80 ± 11 years; 60% male) participated. Falls were recorded on a standardized form, concerning fall injuries, time and place of fall and if the fall was witnessed. Patient characteristics (66 variables) were extracted from medical records and classified into the domains: demographics, activities of daily living, mobility, cognition and behavior, vision and hearing, medical conditions and medication use. We used partial least squares (PLS) regression to determine the relationship between patient characteristics and fall rate. RESULTS A total of 115 falls (5.1 ± 6.7 falls/person/year) occurred over 19 months, with 85% of the residents experiencing a fall, 29% of falls had serious consequences and 28% was witnessed. A combination of impaired mobility, indicators of disinhibited behavior, diabetes, and use of analgesics, beta blockers and psycholeptics were associated with higher fall rates. In contrast, immobility, heart failure, and the inability to communicate were associated with lower fall rates. CONCLUSIONS Falls are frequent and mostly unwitnessed events in long-term care residents with dementia, highlighting the need for more effective and individualized fall prevention. Our analytical approach determined the relationship between a high fall rate and cognitive impairment, related to disinhibited behavior, in combination with mobility disability and fall-risk-increasing-drugs (FRIDs).

Validation of the Dynaport Minimod during sleep: A pilot study

To measure activity during sleep, polysomnography and actigraphy are often used. The DynaPort MiniMod measures movement intensity and body position day and night. The goal was to examine the validity of the DynaPort MiniMod in assessing physical activity and body posture during sleep. In Study A, 10 healthy participants slept with the DynaPort MiniMod and the Actiwatch for one night. In Study B, 8 participants suspected of having Obstructive Sleep Apnoea Syndrome slept for one night with the DynaPort MiniMod and underwent complete polysomnography as part of the typical care protocol. In Study A, there was a significant moderate correlation (r = .70) between the movement scores of the Actiwatch and the DynaPort MiniMod. In Study B, a high intraclass correlation (r = .84) between body posture scores of the DynaPort MiniMod and the polysomnography position sensor was observed. The DynaPort MiniMod is a valid measurement device for physical activity during sleep.

The Association of Medication-Use and Frailty-Related Factors with Gait Performance in Older Patients

The increased fall risk associated with the use of psychotropic drugs might be caused by underlying problems in postural control that are induced by sedative side-effects of these drugs. The current literature on the effects of psychotropics on postural control only examined acute single-drug effects, and included relatively healthy young elderly. Consequently, it is unclear what the impact of the long-term use of these drugs is on gait in frail older persons with polypharmacy. Therefore, it was aimed in the present study to explore the association between the use of psychotropics, multiple other medications, frailty-related parameters and gait performance in older patients. Eighty older persons (79±5.6 years) were recruited. Comorbid diseases, frailty-related parameters, and medication-use were registered. Trunk accelerations during a 3-minute-walking-task were recorded, whereof walking speed, mean stride times, coefficient of variation (CV) of stride times, and step consistency were determined. Multivariate Partial Least Squares (PLS) regression analysis was used to examine the association between population characteristics and medication-use, versus gait parameters. A PLS-model existing of four latent variables was built, explaining 45% of the variance in four gait parameters. Frailty-related factors, being female, and laxative-use were most strongly associated with lower walking speed, higher mean stride times, higher CV of stride times, and less consistent steps. In conclusion, frailty-related parameters were stronger associated with impaired gait performance than the use of psychotropic drugs. Possibly, at a certain frailty-level, the effect of the deterioration in physical functioning in frailty is so large, that the instability-provoking side-effects of psychotropic drugs have less impact on gait.

Multiple gait parameters derived from iPod accelerometry predict age-related gait changes

INTRODUCTION Normative data of how natural aging affects gait can serve as a frame of reference for changes in gait dynamics due to pathologies. Therefore, the present study aims (1) to identify gait variables sensitive to age-related changes in gait over the adult life span using the iPod and (2) to assess if these variables accurately distinguish young (aged 18-45) from healthy older (aged 46-75) adults. METHODS Trunk accelerations were recorded with an iPod Touch in 59 healthy adults during three minutes of overground walking. Gait variables included gait speed and accelerometry-based gait variables (stride, amplitude, frequency, and trajectory-related variables) in the anterior-posterior (AP) and medio-lateral (ML) directions. Multivariate partial least square analysis (PLS) identified variables sensitive to age-related differences in gait. To classify young and old adults, a PLS-discriminant analysis (PLS-DA) was used to test the accuracy of these variables. RESULTS The PLS model explained 42% of variation in age. Influential variables were: mean stride time, phase variability index, root mean square, stride variability, AP sample entropy and ML maximal Lyaponov exponent. PLS-DA classified 83% of the participants correctly with a sensitivity of 83% and specificity of 71%. DISCUSSION Contrary to the frequently reported high gait variability observed in old adults with frailty and fall history, the present study showed that younger compared with older healthy adults had a more variable, less predictable and more symmetrical gait pattern. A model based on a combination of variables reflecting gait dynamics, could distinguish healthy younger adults from older adults.

Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test

Many tests can crudely quantify age-related mobility decrease but instrumented versions of mobility tests could increase their specificity and sensitivity. The Timed-up-and-Go (TUG) test includes several elements that people use in daily life. The test has different transition phases: rise from a chair, walk, 180° turn, walk back, turn, and sit-down on a chair. For this reason the TUG is an often used test to evaluate in a standardized way possible decline in balance and walking ability due to age and or pathology. Using inertial sensors, qualitative information about the performance of the sub-phases can provide more specific information about a decline in balance and walking ability. The first aim of our study was to identify variables extracted from the instrumented timed-up-and-go (iTUG) that most effectively distinguished performance differences across age (age 18–75). Second, we determined the discriminative ability of those identified variables to classify a younger (age 18–45) and older age group (age 46–75). From healthy adults (n = 59), trunk accelerations and angular velocities were recorded during iTUG performance. iTUG phases were detected with wavelet-analysis. Using a Partial Least Square (PLS) model, from the 72-iTUG variables calculated across phases, those that explained most of the covariance between variables and age were extracted. Subsequently, a PLS-discriminant analysis (DA) assessed classification power of the identified iTUG variables to discriminate the age groups. 27 variables, related to turning, walking and the stand-to-sit movement explained 71% of the variation in age. The PLS-DA with these 27 variables showed a sensitivity and specificity of 90% and 85%. Based on this model, the iTUG can accurately distinguish young and older adults. Such data can serve as a reference for pathological aging with respect to a widely used mobility test. Mobility tests like the TUG supplemented with smart technology could be used in clinical practice.

P270: Factors associated with fall rate in psychogeriatric residents

Introduction: Falls in psychogeriatric residents represent a costly but unresolved safety issue. Identifying fall risk factors and their inter-relationship may help to individualize prevention programs and increase the effectiveness. Therefore, we aimed to examine the relationship between patient characteristics and fall rate in psychogeriatric residents. Methods: Twenty nursing home residents with dementia (80±11 years; 60% male) living on a psychogeriatric ward participated. Based on patient records, we identified 66 patient characteristics and extracted the number of falls over 19 months. Patient characteristics represented seven domains: demographics, ADL, mobility, cognition and behaviour, vision and hearing, medical conditions, and drug-use. We evaluated the relationship between patient characteristics and fall rate using multivariate Partial Least Squares regression. Results: A total of 115 falls (5.1±6.7 falls/person year) occurred during the study period. The 66 patient characteristics included in the model explained 96% of the variance in fall rate. Reduced mobility abilities, indicators of disinhibited behavior, diabetes, and use of analgesics, beta blocking agents and psycholeptics were positively associated with fall rate. Whereas immobility, heart failure, and the inability to communicate were negatively associated fall rate. Conclusion: Dementia is often indicated as fall risk factor; however, our results showed that especially cognitive impairment related to disinhibited behaviour was associated with a high fall rate in psychogeriatric residents. Furthermore, immobility and inactivity seemed to decrease fall rate. The analytic approach provided a detailed view of the fall risk factors and their interactions in psychogeriatric residents, enabling more effective fall prevention.