Accelerometry-based gait analysis, an additional objective approach to screen subjects at risk for falling

"Fall Risk Scoring" in Outpatient Gait Analysis: Validation of a New Fall Risk Assessment for Nursing Home Residents

Falls in senior home residents are common. Individual preventive training can lower the fall risk. To detect the need for training, a systematic assessment of the individual fall risk is needed. The aim of this study was thus to assess whether a fall risk score based on free field insole measurements can distinguish between an at-risk group of senior home residents and a healthy young control group. A published fall risk score was used in senior home residents over the age of 75 and a young (< 40 years) control group to determine the individual fall risk. In addition, the fall events over 12 months were assessed. Statistical analysis including ROC analysis was performed to determine the ability of the score to detect participants at heightened fall risk. In total, 18 nursing home residents and 9 young control participants were included. Of the nursing home residents, 15 had at least one fall, with a total of 37 falls recorded over 12 months. In the control group, no falls were recorded. The fall risk score was significantly different between nursing home residents and the control group (9.2 + 3.2 vs. 5.7 ± 2.2). Furthermore, the score significantly differentiated fallers from non-fallers (10.3 ± 1.8 vs. 5.2 ± 2.5), with a cut-off > 7.5 (AUC: 0.95) and a sensitivity of 86.7% (specificity 83.3%). The fall risk score is able to detect the difference between senior nursing home residents and young, healthy controls, as well as between fallers and non-fallers. Its main proof of concept is demonstrated, as based on movement data outside special gait labs, and it can simplify the risk of fall determination in geriatric nursing home residents and can now be used in further, prospective studies.

Modeling the Heterogeneity of Post-Stroke Gait Control in Free-Living Environments Using a Personalized Causal Network

Post-stroke gait control is a complex, often fail to account for the heterogeneity and continuity of gait in existing gait models. Precisely evaluating gait speed adjustability and gait instability in free-living environments is important to understand how individuals with post-stroke gait dysfunction approach diverse environments and contexts. This study aimed to explore individual causal interactions in the free-living gait control of persons with stroke. To this end, fifty persons with stroke wore an accelerometer on the fifth lumbar vertebra (L5) for 24 h in a free-living environment. Individually directed acyclic graphs (DAGs) were generated based on the spatiotemporal gait parameters at contemporaneous and temporal points calculated from the acceleration data. Spectral clustering and Bayesian model comparison were used to characterize the DAGs. Finally, the DAG patterns were interpreted via Bayesian logistic analysis. Spectral clustering identified three optimal clusters from the DAGs. Cluster 1 included persons with moderate stroke who showed high gait asymmetry and gait instability and primarily adjusted gait speed based on cadence. Cluster 2 included individuals with mild stroke who primarily adjusted their gait speed based on step length. Cluster 3 comprised individuals with mild stroke who primarily adjusted their gait speed based on both step length and cadence. These three clusters could be accurately classified based on four variables: Ashman's D for step velocity, Fugl-Meyer Assessment, step time asymmetry, and step length. The diverse DAG patterns of gait control identified suggest the heterogeneity of gait patterns and the functional diversity of persons with stroke. Understanding the theoretical interactions between gait functions will provide a foundation for highly tailored rehabilitation.

Validation of a newly developed low-cost, high-accuracy, camera-based gait analysis system

BACKGROUND

Gait analysis is essential for evaluating locomotor function and fall risk, particularly in the elderly and in various musculoskeletal disorders. Traditional gait analysis systems face challenges such as technical difficulties, high cost, and complexity of use. Therefore, there is a need for a more accessible and cost-effective system with a wider clinical applicability.

RESEARCH QUESTION

This study aimed to validate the newly developed IB-gait® system (InBody, Republic of Korea), a camera-based gait analysis tool, by comparing it against the VICON system.

METHODS

A total of 28 community-dwelling adults without gait abnormalities (mean age 24.9 years) were enrolled in this study. The participants underwent gait analysis at their self-selected speed using VICON and IB-gait® simultaneously. Nine spatiotemporal gait parameters, including stride length (m), step length (m), stride duration (s), double-limb duration (s), stance phase (s), swing phase (s), cadence (velocity × 120/stride length), and gait velocity (m/s) were measured. The agreement between the two systems was tested using Bland-Altman plots and intraclass correlation coefficients (ICC).

RESULTS

The IB-gait® showed a high degree of agreement with the VICON system in most gait parameters. The ICC showed excellent reliability for stride length (0.97), step length (0.92), gait velocity (0.97), cadence (0.97), and stride duration (0.79). However, it showed lower reliability in time-based parameters, including double-limb duration (0.12), stance phase (0.54), swing phase (0.241), and stance/swing phase ratio (0.11).

SIGNIFICANCE

The IB-gait® system appears to be a feasible and cost-effective alternative to VICON system for gait analysis, particularly showing a high level of agreement in the distance-based parameters. Its practicality in clinical settings makes it a valuable tool for widespread use in gait analysis. However, further refinement of time-based parameter measurements and validation in diverse patient populations are needed to enhance its applicability.

Accurate fall risk classification in elderly using one gait cycle data and machine learning

BACKGROUND

Falls among the elderly are a major societal problem. While observations of medium-distance walking using inertial sensors identified potential fall predictors, classifying individuals at risk based on single gait cycles remains elusive. This challenge stems from individual variability and step-to-step fluctuations, making accurate classification difficult.

METHODS

We recruited 44 participants, equally divided into high and low fall-risk groups. A smartphone secured on their second sacral spinous process recorded data during indoor walking. Features were extracted at each gait cycle from a 6-dimensional time series (tri-axial angular velocity and tri-axial acceleration) and classified using the gradient boosting decision tree algorithm.

FINDINGS

Mean accuracy across five-fold cross-validation was 0.936. "Age" was the most influential individual feature, while features related to acceleration in the gait direction held the highest total relative importance when aggregated by axis (0.5365).

INTERPRETATION

Combining acceleration, angular velocity data, and the gradient boosting decision tree algorithm enabled accurate fall risk classification in the elderly, previously challenging due to lack of discernible features. We reveal the first-ever identification of three-dimensional pelvic motion characteristics during single gait cycles in the high-risk group. This novel method, requiring only one gait cycle, is valuable for individuals with physical limitations hindering repetitive or long-distance walking or for use in spaces with limited walking areas. Additionally, utilizing readily available smartphones instead of dedicated equipment has potential to improve gait analysis accessibility.

Biochemical, biomechanical and imaging biomarkers of ischemic stroke: Time for integrative thinking

Stroke is one of the leading causes of adult disability affecting millions of people worldwide. Post-stroke cognitive and motor impairments diminish quality of life and functional independence. There is an increased risk of having a second stroke and developing secondary conditions with long-term social and economic impacts. With increasing number of stroke incidents, shortage of medical professionals and limited budgets, health services are struggling to provide a care that can break the vicious cycle of stroke. Effective post-stroke recovery hinges on holistic, integrative and personalized care starting from improved diagnosis and treatment in clinics to continuous rehabilitation and support in the community. To improve stroke care pathways, there have been growing efforts in discovering biomarkers that can provide valuable insights into the neural, physiological and biomechanical consequences of stroke and how patients respond to new interventions. In this review paper, we aim to summarize recent biomarker discovery research focusing on three modalities (brain imaging, blood sampling and gait assessments), look at some established and forthcoming biomarkers, and discuss their usefulness and complementarity within the context of comprehensive stroke care. We also emphasize the importance of biomarker guided personalized interventions to enhance stroke treatment and post-stroke recovery.

Reduced center of mass acceleration during regular walking with electromyography biofeedback

BACKGROUND

Regular walking in healthy adults is known to be kinematically stable, but it is unclear how to further kinematically stabilize regular walking. Electromyography biofeedback (EMG-BF) during walking improves walking ability in patients. However, the effect of EMG-BF on walking stability in healthy adults is unknown. Therefore, this study aimed to investigate whether EMG-BF enhances the stability of regular walking in healthy adults.

RESEARCH QUESTION

Does the EMG-BF enhance the stability of regular walking in healthy adults?

METHODS

Auditory biofeedback of single muscle activity was given to twelve participants during regular walking. The target muscles were the ankle plantar flexor, ankle dorsiflexor, and knee flexor. We compared the root mean square of the center of mass acceleration (RMS-CoMacc), which represents walking smoothness, between biofeedback conditions.

RESULTS

We found that EMG-BF during regular walking partially reduced the RMS-CoMacc (p = 0.01). In particular, biofeedback of the ankle plantar flexor muscle reduced the RMS-CoMacc in both the anteroposterior and vertical directions. In the mediolateral RMS-CoMacc, no significant difference was found (p = 0.24).

SIGNIFICANCE

Our study is novel because it is the first study to reveal the impact of EMG-BF on the stability of walking among healthy adults. It identifies the key muscles for EMG-BF, potentially leading to the development of a more effective EMG-BF system in the rehabilitation. Especially, biofeedback of the ankle plantar flexor muscle could improve walking stability in both the anteroposterior and vertical directions. The effect of EMG-BF for reducing the RMS-CoMacc during regular walking might depend on the target muscles of biofeedback.

The validity of smartphone-based spatiotemporal gait measurements during walking with and without head turns: Comparison with the GAITRite® system

Smartphone accelerometry has potential to provide clinicians with specialized gait analysis not available in most clinical settings. The Gait&Balance Application (G&B App) uses smartphone accelerometry to assess spatiotemporal gait parameters under two conditions: walking looking straight ahead and walking with horizontal head turns. This study investigated the validity of G&B App gait parameters compared with the GAITRite® pressure-sensitive walkway. Healthy young and older adults (age range 21-85 years) attended a single session where a smartphone was secured over the lumbosacral junction. Data were collected concurrently with the app and GAITRite® systems as participants completed the two walking conditions. Spatiotemporal gait parameters for 54 participants were determined from both systems and agreement evaluated with partial Pearson's correlation coefficients and limits of agreement. The results demonstrated moderate to excellent validity for G&B App measures of step time (rp 0.97, 95 % CI [0.96, 0.98]), walking speed (rp 0.83 [0.78, 0.87]), and step length (rp 0.74, [0.66, 0.80]) when walking looking straight ahead, and results were comparable with head turns. The validity of walking speed and step length measures was influenced by sex and height. G&B App measures of step length variability, step time variability, step length asymmetry, and step time asymmetry had poor validity. The G&B App has potential to provide valid measures of unilateral and bilateral step time, unilateral and bilateral step length, and walking speed, under two walking conditions in healthy young and older adults. Further research should validate this tool in clinical conditions and optimise the algorithm for demographic characteristics.

Watch your step: A pilot study of smartphone use effect on young females' gait performance while walking up and down stairs and escalators

The increasingly ubiquitous use of smartphones has made distracted walking common, not only on flat ground, but also on stairs. Available information regarding changes in gait performance while walking and using a smartphone in different environments is still lacking. We aimed to investigate the differences in gait behavior and subjective walking confidence while walking up and down stairs and escalators, with and without smartphone use. A field experiment involving 32 female adults was conducted at a subway station. Gait parameters collected included step frequency, acceleration root mean square, step variability, step regularity, and step symmetry. The results showed that walking task, walking environment, and walking direction significantly affected gait performance and walking confidence. Overall, playing games or texting while walking down escalators resulted in the lowest walking confidence and the largest gait performance decrement: slower step frequency; reduced root mean square; decreased step regularity and step symmetry; and increased step variability. Step frequency, step variability, and step regularity significantly correlated with walking confidence. Smartphone use while walking on stairs and escalators significantly affects gait behavior and might increase the risk of falls. Interventions and prevention are needed to increase safety education and hazard warnings for the general population.

Weekly minutes of moderate to vigorous physical activity is associated with movement quality in overweight and obese older adults, independent of age

BACKGROUND

Physical activity can improve function and decrease healthcare spending among overweight and obese older adults. Although unstructured physical activity has been related to cardiometabolic improvements, the relationship between unstructured activity and movement quality is unclear.

AIMS

This study aimed to evaluate the association of amount of unstructured free-living moderate-vigorous physical activity (MVPA) with measures of movement quality in overweight and obese older adults.

METHODS

The association of MVPA with movement quality was assessed in 165 overweight and obese older adults (Age: 77.0(8.0) years; Body mass index (BMI): 29.2(5.3) kg/m2). Participants performed overground walking, the Figure of 8 Walk test, and the Five-Times Sit to Stand. Weekly physical activity was measured using a waist-worn Actigraph activity monitor.

RESULTS

Movement quality during straight path [gait speed (ρ = 0.30, p < 0.01), stride length (ρ = 0.33, p < 0.01), double-limb support time (ρ = -0.26, p < 0.01), and gait symmetry (ρ = 0.17, p = 0.02)] and curved path [F8W time (ρ = -0.22, p < 0.01) and steps (ρ = -0.22, p < 0.01)] walking were associated with weekly minutes of MVPA after controlling for age. Five-Times Sit to Stand performance was not significantly associated with weekly minutes of MVPA (ρ = -0.10, p = 0.13).

CONCLUSIONS

Older adults with high BMIs who are less active also demonstrate poorer movement quality, independent of age. Physical activity engagement and task-specific training should be targeted in interventions to promote healthy aging, decrease falls, and delay disability development. Future work should consider the interconnected nature of movement quality with physical activity engagement and investigate if targeting one influences the other.

The Movement Deviation Profile Can Differentiate Faller and Non-Faller Older Adults

BACKGROUND

The World Health Organization considers falls the second leading cause of death by accidental injury worldwide and one of the most frequent complications in older adults during activities of daily living. Several tasks related to fall risk have been individually assessed describing kinematic changes in older adults. The study proposal was to identify which functional task differentiates faller and non-faller older adults using the movement deviation profile (MDP).

METHODS

This cross-sectional study recruited 68 older adults aged ≥60 years by convenience sampling. Older adults were divided into 2 groups: with and without a history of falls (34 older adults in each group). The MDP analyzed the 3-dimensional angular kinematics data of tasks (ie, gait, walking turn, stair ascent and descent, sit-to-stand, and stand-to-sit), and the Z score of the mean MDP identified which task presented the greatest difference between fallers and non-fallers. A multivariate analysis with Bonferroni post hoc verified the interaction between groups considering angular kinematic data and the cycle time of the task. Statistical significance was set at 5% (p < .05).

RESULTS

Z score of the MDPmean showed an interaction between groups (λ = 0.67, F = 5.085, p < .0001). Fallers differed significantly from non-fallers in all tasks and the greatest difference was in stair descent (Z score = 0.89). The time to complete each task was not different between groups.

CONCLUSIONS

The MDP distinguished older adult fallers from non-fallers. The stair descent task should be highlighted because it presented the greatest difference between groups.

Development and Application of a Stability Index Estimation Algorithm Based on Machine Learning for Elderly Balance Ability Diagnosis in Daily Life

BACKGROUND

The stability index estimation algorithm was derived and applied to develop and implement a balance ability diagnosis system that can be used in daily life.

METHODS

The system integrated an approach based on sensory function interaction, called the clinical test of sensory interaction with balance. A capacitance and resistance sensing type force mat was fabricated, and a stability index prediction algorithm was developed and applied using the center of pressure variables. The stability index prediction algorithm derived a center of pressure variable for 103 elderly people by Nintendo Wii Balance Board to predict the stability index of the balance system (Biodex SD), and the accuracy of this approach was confirmed.

RESULTS

As a result of testing with the test set, the linear regression model confirmed that the r-value ranged between 0.943 and 0.983. To confirm the similarity between the WBB and the flexible force mat, each measured center of pressure value was inputted and calculated in the developed regression model, and the result of the correlation coefficient validation confirmed an r-value of 0.96.

CONCLUSION

The system developed in this study will be applicable to daily life in the home in the form of a floor mat.

Assessment of gait and posture characteristics using a smartphone wearable system for persons with osteoporosis with and without falls

We used smartphone technology to differentiate the gait characteristics of older adults with osteoporosis with falls from those without falls. We assessed gait mannerism and obtained activities of daily living (ADLs) with wearable sensor systems (smartphones and inertial measurement units [IMUs]) to identify fall-risk characteristics. We recruited 49 persons with osteoporosis: 14 who had a fall within a year before recruitment and 35 without falls. IMU sensor signals were sampled at 50 Hz using a customized smartphone app (Lockhart Monitor) attached at the pelvic region. Longitudinal data was collected using MoveMonitor+ (DynaPort) IMU over three consecutive days. Given the close association between serum calcium, albumin, PTH, Vitamin D, and musculoskeletal health, we compared these markers in individuals with history of falls as compared to nonfallers. For the biochemical parameters fall group had significantly lower calcium (P = 0.01*) and albumin (P = 0.05*) and higher parathyroid hormone levels (P = 0.002**) than nonfall group. In addition, persons with falls had higher sway area (P = 0.031*), lower dynamic stability (P < 0.001***), gait velocity (P = 0.012*), and were less able to perform ADLs (P = 0.002**). Thus, persons with osteoporosis with a history of falls can be differentiated by using dynamic real-time measurements that can be easily captured by a smartphone app, thus avoiding traditional postural sway and gait measures that require individuals to be tested in a laboratory setting.

Concurrent validity, test-retest reliability, and sensitivity of a PostureRite system measurement on dynamic postural sway and risk of fall in cerebral palsy

BACKGROUND: Accurately diagnosing dynamic postural sway (DPS) is essential for effective and sustainable intervention in children with cerebral palsy (CP). We developed an accurate, inexpensive, and wearable DPS measurement system to measure DPS accurately and consistently during walking and functional activities of daily living. OBJECTIVE: We investigated the validity and reliability of this PostureRite system in children with CP, and the link between PostureRite and clinical measures including gross motor function measure (GMFM), pediatric balance scale (PBS), and fall efficacy scale (FES). METHODS: Twenty-one participants were categorized as follows: 11 healthy adults (3 females, mean age, 25.00±1.00 years) and 10 children with CP (mean age, 11.10±6.28 years). We determined the concurrent validity of PostureRite by comparing DPS data to the gold standard accelerometer measurement results. We determined test-retest reliability by measuring DPS data on three occasions at 2-h intervals. We assessed PostureRite measurement sensitivity to ascertain differences between healthy children and children with CP DPS measurements. RESULTS: Random and mixed intraclass correlation coefficients (ICC2,k and ICC3,k) were obtained; an independent T-test was performed (P < 0.05). Concurrent validity analysis showed a good relationship between the gold standard accelerometer and PostureRite (ICC2,k = 0.973, P < 0.05). Test-retest reliability demonstrated a good relationship across the three repeated measures of the DPS data (ICC3,k = 0.816–0.924, P < 0.05). Independent T-test revealed a significant difference in DPS data between healthy adults and children with CP (P < 0.05). CONCLUSIONS: We developed a portable, wireless, and affordable PostureRite system to measure DPS during gross motor function associated with daily activity and participation, and established the concurrent validity, test-retest reliability as sensitivity, and clinical relevance by comparing the DPS obtained from the participants with and without CP.

Sarcopenia: Body Composition and Gait Analysis

Background

Age-induced sarcopenia negatively affects walking stability and increases the risk of falls, which is the leading cause of accidental death in the elderly.

Objective

This study aimed to analyze and contrast body composition and gait characteristics in those with sarcopenia in relation to healthy controls to shed some light on the prevention of falls in elderly patients with sarcopenia.

Materials and Methods

In this study, 68 community dwellers were scanned by the Hologic QDR-4500A Dual-energy X-ray absorptiometry (DXA). The appendicular lean mass index (ALMI) results were used to distinguish the normal participants from those with sarcopenia: 24 in the sarcopenia group, and 44 into the normal group. The participants were asked to undergo gait analysis on a plantar pressure measurement system. Statistical analysis was conducted to contrast both groups' gait and butterfly parameters from their gait test, and then a gait forward dynamics method was performed to quantify the analysis for both groups.

Results

The ALMI of the female was not related to their age (r = 0.06) while that of the male was weakly related (r = 0.17). Body mass index (BMI) from both groups was normal, although with a statistically greater BMI from the normal group compared with sarcopenia (p &lt; 0.001). Greater values and significant differences were found in step length and stride length from the normal elderly group (p &lt; 0.01), and so was the length of the gait line and single support line (p &lt; 0.05). Gait forward dynamics analysis results showed no motor neural or musculoskeletal disorders in their gait performance from the sarcopenia group.

Conclusion

For the elderly, age did not largely affect the ALMI, BMI, or T-score, but BMI and ALMI were strongly correlated. In this study, significant differences were found in certain gait parameters between the elderly with sarcopenia and the normal elderly, which were related to absolute muscle strength, suggesting that sarcopenia was a disease mainly caused by decreased muscle mass. In addition, when abnormities were identified in step length, stride length, length of gait line, or length of single support line, it is proposed to take a DXA scan to confirm whether the elderly suffer from sarcopenia.

Effectiveness and cost-effectiveness of dynamic bracing versus standard care alone in patients suffering from osteoporotic vertebral compression fractures: protocol for a multicentre, two-armed, parallel-group randomised controlled trial with 12 months of follow-up

INTRODUCTION

Patients with osteoporosis may suffer from a fracture after minimal trauma. Osteoporotic vertebral compression fractures (OVCFs) are among the most common fractures, often leading to substantial pain. There is a need for evidence-based conservative treatment to aid in the management of OVCFs. The objective of this randomised controlled trial (RCT) is to evaluate the effectiveness and cost-effectiveness of dynamic bracing in addition to standard care for improving quality of life (QoL) in patients suffering from an OVCF.

METHODS AND ANALYSIS

Ninety-eight postmenopausal women from two academic and four community hospitals with a recent symptomatic thoracolumbar OVCF will be randomised into either the standard care or dynamic bracing group. In the dynamic bracing group, the Spinova Osteo orthosis will be used in addition to standard care. Standard care comprises pain control with analgesics, physical therapy and osteoporosis medication. The primary outcome parameter is QoL 1 year after inclusion, as measured by the Quality of Life Questionnaire of the European Foundation for Osteoporosis (QUALEFFO-41). Secondary outcome parameters are pain, pain medication used, functional disability, sagittal spinal alignment, recurrence rate of OVCFs and physical activity in daily life. A trial-based economic evaluation consisting of both cost-effectiveness analysis and cost-utility analysis will be performed based on empirical data obtained in the RCT. A process evaluation will assess the feasibility of dynamic bracing. All outcomes will be assessed at baseline, 6 weeks, 3 months, 6 months, 9 months and 12 months.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the Medical Ethics Committee, University Hospital Maastricht and Maastricht University (METC azM/UM) (NL74552.068.20/METC 20-055). Patients will be included only after verification of eligibility and obtaining written informed consent. Results will be disseminated via the Dutch National Osteoporosis Patient Society and via publications and conferences.

TRIAL REGISTRATION NUMBER

NL8746.

Impact of walking states, self-reported daily walking amount and age on the gait of older adults measured with a smart-phone app: a pilot study

BACKGROUND

Smartphones provide a cost-effective avenue for gait assessment among older adults in the community. The purpose of this study is to explore the impact of walking state, self-reported daily walking amount, and age on gait quality, using a smartphone application.

METHODS

One hundred older adult individuals from North China, aged 73.0 ± 7.7 years, voluntarily participated in this study. They performed three walking tests: normal walking, fast walking, and visually impaired walking. Three-dimensional acceleration data for gait were obtained using the smartphone app Pocket Gait. This study used multivariate analysis of variance (MANOVA) to explore the effects of the walking state, self-reported daily walking amount, and age on the step frequency, root mean square (RMS) acceleration, step time variability, regularity, and symmetry.

RESULTS

The walking state, self-reported daily walking amount, and age had statistically significant effects on gait quality. Compared with normal walking, the step frequency, RMS acceleration, variability, and regularity were greater in the fast-walking state, and simulated visually impaired walking did not significantly affect gait quality. Relatively older individuals had a significant decline in gait quality compared to (relatively) younger older adult individuals. Compared with older adults who walked less than 1 km a day, older adults who walked more had better gait quality.

CONCLUSIONS

The walking state, self-reported daily walking amount, and age have a significant effect on the gait quality of older adults. Walking with pigmented sunglasses can be used as a training intervention to improve gait performance. Older adult people who walk less than 1 km/day have worse gait quality compared with their counterparts.

Reliability of Bluetooth inertial sensors for assessing lower limb segment angles and stride length during gait

[Purpose] To assess the agreement between our custom Bluetooth IS system and the gold standard MOCAP system during gait. Bluetooth inertial movement sensors (IS) allow for real-time movement analysis with fewer restrictions than optoelectrical motion capture systems (MOCAP) and more accessibility than wireless IS systems. [Participants and Methods] We collected simultaneous Bluetooth IS and MOCAP data for 16 young participants walking at a self-selected speed. Sensors were placed on the right thigh and shank. Segment angles and stride length were calculated and compared between systems using Pearson’s correlation coefficients (R), intra-class correlation coefficients (ICC), root mean square errors (RMSE), limits of agreement (LOA), and Bland-Altman plots. [Results] R values ranged from 0.371–0.715; ICC values ranged from 0.263–0.770. RMSE was 0.369 m for stride length and ranged from 6.85–13.07° in segment angles. Limits of agreement were −0.01–0.66 m for stride length and ranged from −27.71–20.53° in segment angles. [Conclusion] The Bluetooth IS system showed moderate agreement with MOCAP. Bluetooth IS could be used for reliable gait analysis with fewer space requirements and more portability than wireless IS or MOCAP systems. Bluetooth IS could be used outside of the clinic for real-time monitoring of gait during daily life.

Automatic Recognition and Analysis of Balance Activity in Community-Dwelling Older Adults: Algorithm Validation

BACKGROUND

Clinical mobility and balance assessments identify older adults who have a high risk of falls in clinics. In the past two decades, sensors have been a popular supplement to mobility and balance assessment to provide quantitative information and a cost-effective solution in the community environment. Nonetheless, the current sensor-based balance assessment relies on manual observation or motion-specific features to identify motions of research interest.

OBJECTIVE

The objective of this study was to develop an automatic motion data analytics framework using signal data collected from an inertial sensor for balance activity analysis in community-dwelling older adults.

METHODS

In total, 59 community-dwelling older adults (19 males and 40 females; mean age = 81.86 years, SD 6.95 years) were recruited in this study. Data were collected using a body-worn inertial measurement unit (including an accelerometer and a gyroscope) at the L4 vertebra of each individual. After data preprocessing and motion detection via a convolutional long short-term memory (LSTM) neural network, a one-class support vector machine (SVM), linear discriminant analysis (LDA), and k-nearest neighborhood (k-NN) were adopted to classify high-risk individuals.

RESULTS

The framework developed in this study yielded mean accuracies of 87%, 86%, and 89% in detecting sit-to-stand, turning 360°, and stand-to-sit motions, respectively. The balance assessment classification showed accuracies of 90%, 92%, and 86% in classifying abnormal sit-to-stand, turning 360°, and stand-to-sit motions, respectively, using Tinetti Performance Oriented Mobility Assessment-Balance (POMA-B) criteria by the one-class SVM and k-NN.

CONCLUSIONS

The sensor-based approach presented in this study provided a time-effective manner with less human efforts to identify and preprocess the inertial signal and thus enabled an efficient balance assessment tool for medical professionals. In the long run, the approach may offer a flexible solution to relieve the community's burden of continuous health monitoring.

Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review

BACKGROUND

Higher age and cognitive impairment are associated with a higher risk of falling. Wearable sensor technology may be useful in objectively assessing motor fall risk factors to improve physical exercise interventions for fall prevention. This systematic review aims at providing an updated overview of the current research on wearable sensors for fall risk assessment in older adults with or without cognitive impairment. Therefore, we addressed two specific research questions: 1) Can wearable sensors provide accurate data on motor performance that may be used to assess risk of falling, e.g., by distinguishing between faller and non-faller in a sample of older adults with or without cognitive impairment?; and 2) Which practical recommendations can be given for the application of sensor-based fall risk assessment in individuals with CI? A systematic literature search (July 2019, update July 2020) was conducted using PubMed, Scopus and Web of Science databases. Community-based studies or studies conducted in a geriatric setting that examine fall risk factors in older adults (aged ≥60 years) with or without cognitive impairment were included. Predefined inclusion criteria yielded 16 cross-sectional, 10 prospective and 2 studies with a mixed design.

RESULTS

Overall, sensor-based data was mainly collected during walking tests in a lab setting. The main sensor location was the lower back to provide wearing comfort and avoid disturbance of participants. The most accurate fall risk classification model included data from sit-to-walk and walk-to-sit transitions collected over three days of daily life (mean accuracy = 88.0%). Nine out of 28 included studies revealed information about sensor use in older adults with possible cognitive impairment, but classification models performed slightly worse than those for older adults without cognitive impairment (mean accuracy = 79.0%).

CONCLUSION

Fall risk assessment using wearable sensors is feasible in older adults regardless of their cognitive status. Accuracy may vary depending on sensor location, sensor attachment and type of assessment chosen for the recording of sensor data. More research on the use of sensors for objective fall risk assessment in older adults is needed, particularly in older adults with cognitive impairment.

TRIAL REGISTRATION

This systematic review is registered in PROSPERO ( CRD42020171118 ).

Validity of Inertial Sensors for Assessing Balance Kinematics and Mobility during Treadmill-Based Perturbation and Dance Training

Inertial sensors (IS) enable the kinematic analysis of human motion with fewer logistical limitations than the silver standard optoelectronic motion capture (MOCAP) system. However, there are no data on the validity of IS for perturbation training and during the performance of dance. The aim of this present study was to determine the concurrent validity of IS in the analysis of kinematic data during slip and trip-like perturbations and during the performance of dance. Seven IS and the MOCAP system were simultaneously used to capture the reactive response and dance movements of fifteen healthy young participants (Age: 18-35 years). Bland Altman (BA) plots, root mean square errors (RMSE), Pearson's correlation coefficients (R), and intraclass correlation coefficients (ICC) were used to compare kinematic variables of interest between the two systems for absolute equivalency and accuracy. Limits of agreements (LOA) of the BA plots ranged from -0.23 to 0.56 and -0.21 to 0.43 for slip and trip stability variables, respectively. The RMSE for slip and trip stabilities were from 0.11 to 0.20 and 0.11 to 0.16, respectively. For the joint mobility in dance, LOA varied from -6.98-18.54, while RMSE ranged from 1.90 to 13.06. Comparison of IS and optoelectronic MOCAP system for reactive balance and body segmental kinematics revealed that R varied from 0.59 to 0.81 and from 0.47 to 0.85 while ICC was from 0.50 to 0.72 and 0.45 to 0.84 respectively for slip-trip perturbations and dance. Results of moderate to high concurrent validity of IS and MOCAP systems. These results were consistent with results from similar studies. This suggests that IS are valid tools to quantitatively analyze reactive balance and mobility kinematics during slip-trip perturbation and the performance of dance at any location outside, including the laboratory, clinical and home settings.

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.

Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review

In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of the motor skill of walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the body motion's translation during walking. Gait measures from accelerometers can enrich measurements of walking and motor performance. This review article will categorize the aspects of the motor skill of walking and review how trunk-acceleration gait measures during walking can be mapped to motor skill aspects, satisfying a clinical need to understand how well accelerometer measures assess gait. We will clarify how to leverage more complicated acceleration measures to make accurate motor skill decline predictions, thus furthering fall research in older adults.

Foreseeing future falls with accelerometer features in active community-dwelling older persons with no recent history of falls

BACKGROUND

Acceleration sensors are a viable option for monitoring gait patterns and its application on monitoring falls and risk of falling. However the literature still lacks prospective studies to investigate such risk before the occurrence of falls.

OBJECTIVE

To investigate features extracted from accelerometer signals with the purpose of predicting future falls in individuals with no recent history of falls.

METHODS

In this study we investigate the risk of fall in active and healthy community-dwelling living older persons with no recent history of falls, using a single accelerometer and variants of the Timed Up and Go (TUG) test. A prospective study was conducted with 74 healthy non-fallers older persons. After collecting acceleration data from the participants at the baseline, the occurrence of falls (outcome) was monitored quarterly during one year. A set of frequency features were extracted from the signal and their ability to predict falls was evaluated.

RESULTS

The best individual feature result shows an accuracy of 0.75, sensitivity of 0.71 and specificity of 0.76. A fusion of the three best features increases the sensitivity to 0.86. On the other hand, the cut-off points of the TUG seconds, often used to assess fall risk, did not demonstrate adequate sensitivity.

CONCLUSION

The results confirms previous evidence that accelerometer features can better estimate fall risk, and support potential applications that try to infer falls risk in less restricted scenarios, even in a sample stratified by age and gender composed of active and healthy community-dwelling living older persons.

Development of a dynamic fall risk profile in elderly nursing home residents: A free field gait analysis based study

Falls in nursing home residents are associated with a significant individual and socioeconomic burden of disease. To trigger and tailor individual intervention programs, solid early detection measures of residents at risk are needed. Aim of this study was thus to test the capability of a free field gait analysis insole to determine its usefulness in determining fall risk. In an observational study gait data of 22 nursing home residents over the age of 75 years was collected over one week with a measuring insole. Clinical scores were performed at baseline (POMA; DGI, TUG). For 6 months before and after the insole measurement, the fall events per resident were recorded. Correlation analysis as well as receiver operating characteristic curve analysis were performed. The average resident age was 88.2 years (range 78-99), 15 had at least one fall event. There was no significant correlation between clinical assessment and fall risk. Moderate correlations between different temporospatial parameters and fall risk were seen. Pressure distribution during gait was markedly changed in fallers. Differences between fallers and non-fallers as well as cut off values for increased fall risk in the ROC analysis could be determined. The introduced measurement protocol suggests that patients at risk for falling can be detected without any additional office visits. Based on the introduced protocol in a limited patient setting, further large scale studies should now determine the effect of prevention measures triggered by gait analysis, the specific risk reduction and the associated personal and socioeconomic advantages.

Percentiles and Reference Values for Accelerometric Gait Assessment in Women Aged 50-80 Years

Background: The identification of factors that alter postural stability is fundamental in the design of interventions to maintain independence and mobility. This is especially important for women because of their longer life expectancy and higher incidence of falls than in men. We constructed the percentile box charts and determined the values of reference for the accelerometric assessment of the gait in women. Methods: We used a cross-sectional study with 1096 healthy adult women, who were asked to walk a distance of 20 m three times. Results: In all of the variables, a reduction in the magnitude of accelerations was detected as the age of the group advanced. The box charts show the amplitude of the interquartile ranges, which increases as the age of the participants advances. In addition, the interquartile ranges were greater in the variables that refer to the maximum values of the accelerations. Conclusions: The values obtained can be used to assess changes in gait due to aging, trauma and orthopaedic alterations that may alter postural stability and neurodegenerative processes that increase the risk of falling.

Changes in symmetry during gait in adults with Prader-Willi syndrome

Most studies on locomotion of individuals with the Prader-Willi Syndrome (PWS) have been performed in a laboratory setting using quantitative motion analysis. Recently, wireless inertial sensors have been successfully employed for gait analysis in different pathological states with the advantages of reproducing a testing condition very close to those encountered in daily living. Using such devices, it is possible not only to characterize the conventional spatio-temporal parameters, but also extract information on further less conventional metrics, such as the harmonic ratio (HR), a measure of step-to-step symmetry based on trunk acceleration processing. In the present study, this technique was used to quantify gait parameters during level walking in 20 adults with PWS who were compared to 20 unaffected individuals. While no differences between the two groups were found in terms of spatio-temporal parameters, individuals with PWS exhibited significantly reduced values of HR in the antero-posterior and vertical directions. Such results, which indicate a poorer gait symmetry in PWS, suggest that upper body accelerations, as well as HR, provide novel information on gait in people with PWS that could not be extracted from spatio-temporal parameters only.

Wearable sensors can reliably quantify gait alterations associated with disability in people with progressive multiple sclerosis in a clinical setting

Gait disability in people with progressive multiple sclerosis (MS) is difficult to quantify using existing clinical tools. This study aims to identify reliable and objective gait-based biomarkers to monitor progressive multiple sclerosis (MS) in clinical settings. During routine clinical visits, 57 people with secondary progressive MS and 24 healthy controls walked for 6 minutes wearing three inertial motion sensors. Fifteen gait measures were computed from the sensor data and tested for between-session reliability, for differences between controls and people with moderate and severe MS disability, and for correlation with Expanded Disability Status Scale (EDSS) scores. The majority of gait measures showed good to excellent between-session reliability when assessed in a subgroup of 23 healthy controls and 25 people with MS. These measures showed that people with MS walked with significantly longer step and stride durations, reduced step and stride regularity, and experienced difficulties in controlling and maintaining a stable walk when compared to controls. These abnormalities significantly increased in people with a higher level of disability and correlated with their EDSS scores. Reliable and objective gait-based biomarkers using wearable sensors have been identified. These biomarkers may allow clinicians to quantify clinically relevant alterations in gait in people with progressive MS within the context of regular clinical visits.

Personalized Template-Based Step Detection From Inertial Measurement Units Signals in Multiple Sclerosis

Background: Objective gait assessment is key for the follow-up of patients with progressive multiple sclerosis (pMS). Inertial measurement units (IMUs) provide reliable and yet easy quantitative gait assessment in routine clinical settings. However, to the best of our knowledge, no automated step-detection algorithm performs well in detecting severely altered pMS gait. Method: This article elaborates on a step-detection method based on personalized templates tested against a gold standard. Twenty-two individuals with pMS and 10 young healthy subjects (HSs) were instructed to walk on an electronic walkway wearing synchronized IMUs. Templates were derived from the IMU signals by using Initial and Final Contact times given by the walkway. These were used to detect steps from other gait trials of the same individual (intra-individual template-based detection, IITD) or another participant from the same group (pMS or HS) (intra-group template-based detection, IGTD). All participants were seen twice with a 6-month interval, with two measurements performed at each visit. Performance and accuracy metrics were computed, along with a similarity index (SId), which was computed as the mean distance between detected steps and their respective closest template. Results: For HS participants, both the IITD and the IGTD algorithms had precision and recall of 1.00 for detecting steps. For pMS participants, precision and recall ranged from 0.94 to 1.00 for IITD and 0.85 to 0.95 for IGTD depending on the level of disability. The SId was correlated with performance and the accuracy of the result. An SId threshold of 0.957 (IITD) and 0.963 (IGTD) could rule out decreased performance (F-measure ≤ 0.95), with negative predictive values of 0.99 and 0.96 with the IITD and IGTD algorithms. Also, the SId computed with the IITD and IGTD algorithms could distinguish individuals showing changes at 6-month follow-up. Conclusion: This personalized step-detection method has high performance for detecting steps in pMS individuals with severely altered gait. The algorithm can be self-evaluating with the SI, which gives a measure of the confidence the clinician can have in the detection. What is more, the SId can be used as a biomarker of change in disease severity occurring between the two measurement times.

Percentiles and Reference Values for the Accelerometric Assessment of Static Balance in Women Aged 50-80 Years

The identification of factors that alter postural stability is fundamental in the design of interventions to maintain independence and mobility. This is especially important for women because of their longer life expectancy and higher incidence of falls compared to men. The objective of this study was to construct the percentile box charts and determine the values of reference for the accelerometric assessment of the static balance in women. For this, an observational and cross-sectional study with a sample composed of 496 women (68.8 ± 10.4 years old) was conducted. The measurement of accelerations used a triaxial accelerometer during three tests: two tests on the ground in monopodal support and a test on a mat with monopodal support for 30 s each. In all of the variables, an increase in the magnitude of the accelerations was detected as the age advanced. The box charts of the percentiles of the tests show the amplitude of the interquartile ranges, which increased as the age advanced. The values obtained can be used to assess changes in static balance due to aging, trauma and orthopaedic and neurodegenerative alterations that may alter postural stability and increase the risk of falling.

Wearable inertial sensors to measure gait and posture characteristic differences in older adult fallers and non-fallers: A scoping review

BACKGROUND

Wearable inertial sensors have grown in popularity as a means of objectively assessing fall risk. This review aimed to identify gait and posture differences among older adult fallers and non-fallers which can be measured with the use of wearable inertial sensors. In addition to describing the number of sensors used to obtain measures, the concurrent anatomical locations, how these measures compare to current forms of clinical fall risk assessment tests and the setting of tests.

METHODS

Following the development of a rigorous search strategy, MEDLINE, Web of Science, Cochrane, EMBASE, PEDro, and CINAHL were systematically searched for studies involving the use of wearable inertial sensors, to determine gait and postural based differences among fallers or those at high fall risk compared with non-fallers and low fall risk adults aged 60 years and older.

RESULTS

Thirty five papers met the inclusion criteria. One hundred and forty nine gait and posture characteristic differences were identified using wearable inertial sensors. There were sensor derived measures which significantly and strongly correlated with traditional clinical tests. The use of a single wearable inertial sensor located at the lower posterior trunk, was most the most effective location and enough to ascertain multiple pertinent fall risk factors.

CONCLUSION

This review identified the capabilities of identifying fall risk factors among older adults with the use of wearable inertial sensors. The lightweight portable nature makes inertial sensors an effective tool to be implemented into clinical fall risk assessment and continuous unsupervised home monitoring, in addition to, outdoor testing.

Optimization and Validation of an Adjustable Activity Classification Algorithm for Assessment of Physical Behavior in Elderly

Due to a lack of transparency in both algorithm and validation methodology, it is difficult for researchers and clinicians to select the appropriate tracker for their application. The aim of this work is to transparently present an adjustable physical activity classification algorithm that discriminates between dynamic, standing, and sedentary behavior. By means of easily adjustable parameters, the algorithm performance can be optimized for applications using different target populations and locations for tracker wear. Concerning an elderly target population with a tracker worn on the upper leg, the algorithm is optimized and validated under simulated free-living conditions. The fixed activity protocol (FAP) is performed by 20 participants; the simulated free-living protocol (SFP) involves another 20. Data segmentation window size and amount of physical activity threshold are optimized. The sensor orientation threshold does not vary. The validation of the algorithm is performed on 10 participants who perform the FAP and on 10 participants who perform the SFP. Percentage error (PE) and absolute percentage error (APE) are used to assess the algorithm performance. Standing and sedentary behavior are classified within acceptable limits (±10% error) both under fixed and simulated free-living conditions. Dynamic behavior is within acceptable limits under fixed conditions but has some limitations under simulated free-living conditions. We propose that this approach should be adopted by developers of activity trackers to facilitate the activity tracker selection process for researchers and clinicians. Furthermore, we are convinced that the adjustable algorithm potentially could contribute to the fast realization of new applications.

Are cost-effective technologies feasible to measure gait in older adults? A systematic review of evidence-based literature

BACKGROUND

Unrestricted by time and place, innovative technologies seem to provide cost-effective solutions for gait assessment in older adults.

OBJECTIVE

The objective of this study is to provide an overview of gait assessment for older adults by investigating critical gait characteristics of older adults, discussing advantages and disadvantages of the current gait assessment technologies, as well as device applicability.

METHODS

The Preferred Reporting Item for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed during the review. Inclusion criteria were: (1) Sample consisting of adults older than 60 years; (2) qualitative, quantitative, or mixed-method researches using one or more specific gait assessment technologies; and (3) publication in English between 2000 and 2018.

RESULTS

In total, twenty-one studies were included. Gait speed, stride length, frequency, acceleration root mean square, step-to-step consistency, autocorrelation, harmonic ratio were reported in the existing literatures to be associated with falls. The enrolled studies address the use of pedometer, wearable accelerometer-based devices, Kinect, Nintendo Wii Balance Board as cost-effective gait assessment technologies.

CONCLUSIONS

Gait parameters and assessment approaches for older adults are diverse. Cost-effective technologies such as a wearable accelerometer-based device, Kinect, and the Nintendo Wii Balance Board provide potential alternatives for gait assessment with acceptable validity and reliability compared with sophisticated devices. The popularity and development of cost-effective devices have made large-scale data collection for gait assessment possible in the daily environment. Further study could involve older adults and their family members/caregivers in use of these technologies to design elderly-friendly products.

Fall detection and fall risk assessment in older person using wearable sensors: A systematic review

BACKGROUND

wearable sensors are often used to acquire data for gait analysis as a strategy to study fall events, due to greater availability of acquisition platforms, and advances in computational intelligence. However, there are no review papers addressing the three most common types of applications related to fall using sensors, namely: fall detection, fallers classification and fall risk screening.

OBJECTIVE

To identify the state of art of fall-related events detection in older person using wearable sensors, as well as the main characteristics of the studies in the literature, pointing gaps for future studies.

METHODS

A systematic review design was used to search peer-reviewed literature on fall detection and risk in elderly through inertial sensors, published in English, Portuguese, Spanish or French between August 2002 and June 2019. The following questions are investigated: the type of sensors and their sampling rate, the type of signal and data processing employed, the scales and tests used in the study and the type of application.

RESULTS

We identified 608 studies, from which 29 were included. The accelerometer, with sampling rate 50 or 100 Hz, allocated in the waist or lumbar was the most used sensor setting. Methods comparing features or variables extracted from the accelerometry signal are the most common, and fall risk screening the most observed application.

CONCLUSION

This review identifies the main elements to be addressed in studies on the detection of events related to falls in the elderly and may help in future studies on the subject. However, some aspects are still no reach consensus in the literature such as the size of the sample to be studied, the population under study and how to acquire data for each application.

Analyzing the Use of Accelerometers as a Method of Early Diagnosis of Alterations in Balance in Elderly People: A Systematic Review

Alterations of balance are a growing public health problem as they affect one in three adults over the age of 65, and one in two over the age of 80. Identifying the factors that affect postural stability is essential in designing specific interventions to maintain the independence and mobility of older people. The aim of this review was to understand the use of accelerometers in order to assess the balance in older people. Analyzing the most appropriate evaluation methodology and protocolizing it will optimize the processes of early identification of balance alterations. However, quantitative assessment methods of balance are usually limited to a laboratory environment, a factor that can be overcome by accelerometers. A systematic search was carried out across eight databases where accelerometers were employed to assess balance in older people. Articles were excluded if they focused on sensor design and did not measure balance or apply the technology on targeted participants. A total of 19 articles were included for full-text analysis, where participants took part in the balance evaluation monitored by accelerometers. The analysis of spatio-temporal parameters and the magnitude of the accelerations recorded by the devices were the most common study variables. Accelerometer usage has potential to positively influence interventions based on physical exercise to improve balance and prevent falls in older people.

Development and validation of Comprehensive Gait Assessment using InerTial Sensor score (C-GAITS score) derived from acceleration and angular velocity data at heel and lower trunk among community-dwelling older adults

Background

Although some gait parameters from inertial sensors have been shown to be associated with important clinical issues, because of controversial results, it remains uncertain which parameters for which axes are clinically valuable. Following the idea that a comprehensive score obtained by summing various gait parameters would sensitively reflect declines in gait performance, we developed a scoring method for community-dwelling older adults, the Comprehensive Gait Assessment using InerTial Sensor score (C-GAITS score). The aim of this study was to examine the internal consistency and the construct validity of this method.

Methods

In this cross-sectional study, the gait performance of 378 community-dwelling older people (mean age = 71.7 ± 4.2 years, 210 women) was assessed using inertial sensors attached to the heel and lower trunk. Participants walked along a 15-m walkway, and accelerations, angular velocity, and walking time were measured. From these data, walking speed, mean stride time, coefficients of variation of stride time and swing time, and autocorrelation coefficients and harmonic ratios of acceleration in vertical, mediolateral, and anteroposterior directions at the lower trunk were calculated. Scoring was performed based on quartile by gender (i.e., scored from 0 to 3) for each of the 10 gait parameters. The C-GAITS score was the sum of these scores (range: 0–30). Lower extremity strength, balance function, fall history, and fear of falling were also assessed.

Results

An exploratory factor analysis revealed that the C-GAITS score yielded four distinct factors explaining 57.1% of the variance. The Cronbach’s alpha coefficient was 0.77. A single linear regression analysis showed a significant relationship between total C-GAITS score and walking speed (adjusted R² = 0.28). Results from bivariate comparisons using unpaired t-tests showed that the score was significantly related to age (p = 0.002), lower extremity strength (p = 0.007), balance function (p <  0.001), fall history (p = 0.04), and fear of falling (p <  0.001).

Conclusions

Good internal consistency and appropriate construct validity of the C-GAITS score were confirmed among community-dwelling older adults. The score might be useful in clinical settings because of ease of use and interpretation and capability of capturing functional decline.

Wearable Inertial Sensors for Fall Risk Assessment and Prediction in Older Adults: A Systematic Review and Meta-Analysis

Wearable inertial sensors have been widely investigated for fall risk assessment and prediction in older adults. However, heterogeneity in published studies in terms of sensor location, task assessed and features extracted is high, making challenging evidence-based design of new studies and/or real-life applications. We conducted a systematic review and meta-analysis to appraise the best available evidence in the field. Namely, we applied established statistical methods for the analysis of categorical data to identify optimal combinations of sensor locations, tasks, and feature categories. We also conducted a meta-analysis on sensor-based features to identify a set of significant features and their pivot values. The results demonstrated that with a walking test, the most effective feature to assess the risk of falling was the velocity with the sensor placed on the shins. Conversely, during quite standing, linear acceleration measured at the lower back was the most effective combination of feature-placement. Similarly, during the sit-to-stand and/or the stand-to-sit tests, linear acceleration measured at the lower back seems to be the most effective feature-placement combination. The meta-analysis demonstrated that four features resulted significantly higher in fallers: the root-mean-square acceleration in the mediolateral direction during quiet standing with eyes closed [Mean Difference (MD): 0.01 g; 95% Confidence Interval (CI95%): 0.006 to 0.014]; the number of steps (MD: 1.638 steps; CI95%: 0.384 to 2.892) and total time (MD: 2.274 seconds; CI95%: 0.531 to 4.017) to complete the timed up and go test; and the step time (MD: 0.053; CI95%: 0.012 to 0.095; p = 0.01) during walking.

A Principal Components Analysis Approach to Quantifying Foot Clearance and Foot Clearance Variability

Low foot clearance and high variability may be related to falls risk. Foot clearance is often defined as the local minimum in toe height during swing; however, not all strides have this local minimum. The primary purpose of this study was to identify a nondiscrete measure of foot clearance during all strides, and compare discrete and nondiscrete measures in ability to rank individuals on foot clearance and variability. Thirty-five participants (young adults [n = 10], older fallers [n = 10], older nonfallers [n = 10], and stroke survivors [n = 5]) walked overground while lower extremity 3D kinematics were recorded. Principal components analysis (PCA) of the toe height waveform yielded representation of toe height when it was closest to the ground. Spearman's rank order correlation assessed the association of foot clearance and variability between PCA and discrete variables, including the local minimum. PCA had significant (P < .05) moderate or strong associations with discrete measures of foot clearance and variability. An approximation of the discrete local minimum had a weak association with PCA and other discrete measures of foot clearance. A PCA approach to quantifying foot clearance can be used to identify the behavioral components of toe height when it is closest to the ground, even for strides without a local minimum.

Mobility related physical and functional losses due to aging and disease - a motivation for lower limb exoskeletons

BACKGROUND

Physical and functional losses due to aging and diseases decrease human mobility, independence, and quality of life. This study is aimed at summarizing and quantifying these losses in order to motivate solutions to overcome them with a special focus on the possibilities by using lower limb exoskeletons.

METHODS

A narrative literature review was performed to determine a broad range of mobility-related physical and functional measures that are affected by aging and selected cardiovascular, respiratory, musculoskeletal, and neurological diseases.

RESULTS

The study identified that decreases in limb maximum muscle force and power (33% and 49%, respectively, 25-75 yrs) and in maximum oxygen consumption (40%, 20-80 yrs) occur for older adults compared to young adults. Reaction times more than double (18-90 yrs) and losses in the visual, vestibular, and somatosensory systems were reported. Additionally, we found decreases in steps per day (75%, 60-85 yrs), maximum walking speed (24% 25-75 yrs), and maximum six-minute and self-selected walking speed (38% and 21%, respectively, 20-85 yrs), while we found increases in the number of falls relative to the number of steps per day (800%), injuries due to falls (472%, 30-90 yrs) and deaths caused by fall (4000%, 65-90 yrs). Measures were identified to be worse for individuals with impaired mobility. Additional detrimental effects identified for them were the loss of upright standing and locomotion, freezing in movement, joint stress, pain, and changes in gait patterns.

DISCUSSION

This review shows that aging and chronic conditions result in wide-ranging losses in physical and sensory capabilities. While the impact of these losses are relatively modest for level walking, they become limiting during more demanding tasks such as walking on inclined ground, climbing stairs, or walking over longer periods, and especially when coupled with a debilitating disease. As the physical and functional parameters are closely related, we believe that lost functional capabilities can be indirectly improved by training of the physical capabilities. However, assistive devices can supplement the lost functional capabilities directly by compensating for losses with propulsion, weight support, and balance support.

CONCLUSIONS

Exoskeletons are a new generation of assistive devices that have the potential to provide both, training capabilities and functional compensation, to enhance human mobility.

Effects of Compliant Flooring on Dynamic Balance and Gait Characteristics of Community-dwelling Older Persons

BACKGROUND

Compliant flooring while providing the impact force attenuation in the event of falls, its low stiffness characteristic might impair balance and gait which consequently resulted in an increase in the risk of falling.

OBJECTIVE

To investigate the effects of compliant flooring on dynamic balance and gait performance of older adults under challenging conditions.

DESIGN AND PARTICIPANTS

A cross-sectional designed with repeated measured. Thirty five community-dwelling older adults (mean age 74.91 ± 6.51 yrs) participated in this study.

MEASUREMENT

Modified Dynamic Gait Index (mDGI) and Timed Up and Go (TUG) were used to assess dynamic balance. Spatio-temporal gait parameters were measured under comfortable and maximal speed. All tests were administered on the vinyl and compliant flooring in random order.

RESULTS

The time taken to complete TUG and the mDGI scores were similar between the two flooring types (p ≥ 0.05). Overall, gait characteristics were comparable when walking on the compliant and vinyl flooring for both speeds except for swing time, step time, and cadence.

CONCLUSION

The present study demonstrated that compliant flooring did not significantly affect dynamic balance and had minimal effects on gait characteristics. The compliant flooring appears to be safe for installing in self-ambulating older adult's home.

Identifying trippers and non-trippers based on knee kinematics during obstacle-free walking

Trips are a major cause of falls. Sagittal-plane kinematics affect clearance between the foot and obstacles, however, it is unclear which kinematic measures during obstacle-free walking are associated with avoiding a trip when encountering an obstacle. The purpose of this study was to determine kinematic factors during obstacle-free walking that are related to obstacle avoidance ability. It was expected that successful obstacle avoidance would be associated with greater peak flexion/dorsiflexion and range of motion (ROM), and differences in timing of peak flexion/dorsiflexion during swing of obstacle-free walking for the hip, knee and ankle. Three-dimensional kinematics were recorded as 35 participants (young adults age 18-45 (N = 10), older adults age 65+ without a history of falls (N = 10), older adults age 65+ who had fallen in the last six months (N = 10), and individuals who had experienced a stroke more than six months earlier (N = 5)) walked on a treadmill, under obstacle-free walking conditions with kinematic features calculated for each stride. A separate obstacle avoidance task identified trippers (multiple obstacle contact) and non-trippers. Linear discriminant analysis with sequential feature selection classified trippers and non-trippers based on kinematics during obstacle-free walking. Differences in classification performance and selected features (knee ROM and timing of peak knee flexion during swing) were evaluated between trippers and non-trippers. Non-trippers had greater knee ROM (P = .001). There was no significant difference in classification performance (P = .193). Individuals with reduced knee ROM during obstacle-free walking may have greater difficulty avoiding obstacles.

Evaluation of the Tinetti score and fall risk assessment via accelerometry-based movement analysis

Gait and balance disorders are among the main predisposing factors of falls in elderly. Clinical scales are widely employed to assess the risk of falling, but they require trained personnel. We investigate the use of objective measures obtained from a wearable accelerometer to evaluate the fall risk, determined by the Tinetti clinical scale. Seventy-nine patients and eleven volunteers were enrolled in two rehabilitation centers and underwent a full Tinetti test, while wearing a triaxial accelerometer at the chest. Tinetti scores were assessed by expert physicians and those subjects with a score ≤18 were considered at high risk. First, we analyzed 21 accelerometer features by means of statistical tests and correlation analysis. Second, one regression and one classification problem were designed and solved using a linear model (LM) and an artificial neural network (ANN) to predict the Tinetti outcome. Pearson's correlation between the Tinetti score and a subset of 9 features (mainly related with standing and walking) was 0.71. The misclassification error of high risk patient was 0.21 and 0.11, for LM and ANN, respectively. The work might foster the development of a new generation of applications meant to monitor the time evolution of the fall risk using low cost devices at home.

Quantification of Axial Abnormality Due to Cerebellar Ataxia with Inertial Measurements

Cerebellar Ataxia (CA) leads to deficiencies in muscle movement and lack of coordination that is often manifested as gait and balance disabilities. Conventional CA clinical assessments are subjective, cumbersome and provide less insight into the functional capabilities of patients. This cross-sectional study investigates the use of wearable inertial sensors strategically positioned on the front-chest and upper-back locations during the Romberg and Trunk tests for objective assessment of human postural balance due to CA. The primary aim of this paper is to quantify the performance of postural stability of 34 patients diagnosed with CA and 22 healthy subjects as controls. Several forms of entropy descriptions were considered to uncover characteristics of movements intrinsic to CA. Indeed, correlation with clinical observation is vital in ascertaining the validity of the inertial measurements in addition to capturing unique features of movements not typically observed by the practicing clinician. Both of these aspects form an integral part of the underlying objective assessment scheme. Uncertainty in the velocity contained a significant level of information with respect to truncal instability and, based on an extensive clustering and discrimination analysis, fuzzy entropy was identified as an effective measure in characterising the underlying disability. Front-chest measurements demonstrated a strong correlation with clinical assessments while the upper-back measurements performed better in classifying the two cohorts, inferring that the standard clinical assessments are relatively influenced by the frontal observations. The Romberg test was confirmed to be an effective test of neurological diagnosis as well as a potential candidate for objective assessment resulting in a significant correlation with the clinical assessments. In contrast, the Trunk test is observed to be relatively less informative.

Application of smart bracelet to monitor frailty-related gait parameters of older Chinese adults: A preliminary study

AIM

Smart bracelets are popular today. Based on their built-in motion sensors, they can serve as a cost-effective method of gait assessment in home-based care. Few studies have applied smart bracelets in the gait assessment of older Chinese adults. The present study aimed to: (i) establish reference gait parameters of older Chinese adults using smart bracelets under single and dual task; and (ii) explore the differences in gait parameters among non-frail and pre-frail Chinese older adults.

METHODS

A total of 50 community-dwelling older Chinese adults aged ≥50 years wore a smart bracelet sensor in the L3 region of the back and underwent a 10-m walking test under single- and dual-task conditions. Participants were preliminarily classified into non-frail and pre-frail groups based on the Fatigue, Resistance, Ambulation, Illnesses and Loss of Weight scale. Gait parameters including average walking speed, step frequency, root mean square (RMS), acceleration amplitude variability, step variability, step regularity and step symmetry were calculated based on the data exported from the bracelet.

RESULTS

Multivariate analysis of covariance (mancova) analysis showed that older adults had significantly decreased speed and step frequency (P < 0.05) under the dual cognitive task condition. Pre-frail older adults showed significantly decreased speed, mediolateral RMS, vertical RMS, anteroposterior RMS, vertical amplitude variability and vertical step regularity compared with non-frail older adults (P < 0.05).

CONCLUSIONS

The present study suggested that the decline in gait parameters as a result of frailty could be detected by the smart bracelet sensor. Geriatr Gerontol Int 2018; 18: 1366-1371.

Assessing gait parameters with accelerometer-based methods to identify older adults at risk of falls: a systematic review

PURPOSE

The purpose of this study was to perform a systematic review to assess the utility of accelerometric methods to identify older adults at risk of falls.

METHODS

The Preferred Reporting Item for Systematic review and Meta-Analysis (PRISMA) guidelines were followed during all steps of this systematic review. Cross sectional and longitudinal studies assessing gait parameters in older adults using accelerometric devices, and comparing groups based on the risk of falls or fall history were identified from studies published in the MEDLINE, SCOPUS and Cochrane Database of Systematic Reviews databases between January 1996 and January 2017. Study selection and data extraction were performed independently by two reviewers. The quality of the methodology used in the studies included was assessed using the Newcastle-Ottawa Scale.

RESULTS

In total, 354 references were identified through the database search. After selection, ten studies were included in this systematic review. According to the cross sectional studies, people who fall or are at risk of fall are slower, and walk with shorter steps, lower step frequency, worse stride and step regularity in terms of time, position and acceleration profiles. One longitudinal study suggests considering harmonic ratio of upper trunk acceleration in the vertical plane. Two other longitudinal studies highlight the importance of considering more than one gait parameter, and sophisticated statistical tools to discern older adults at risk for future fall(s).

CONCLUSION

This systematic review essentially highlights the lack of available literature providing strong evidence that gait parameters obtained using acceleration-based methods could be useful to discern older people at risk of fall. Available literature is encouraging, but further high quality studies are needed to highlight the cross-sectional and longitudinal relationships between gait parameters and falls in older adults.

Accelerometer-based predictive models of fall risk in older women: a pilot study

Current clinical methods of screening older adults for fall risk have difficulties. We analyzed data on 67 women (mean age = 77.5 years) who participated in the Objective Physical Activity and Cardiovascular Health (OPACH) study within the Women’s Health Initiative and in an accelerometer calibration substudy. Participants completed the short physical performance battery (SPPB), questions about falls in the past year, and a timed 400-m walk while wearing a hip triaxial accelerometer (30 Hz). Women with SPPB ≤ 9 and 1+reported falls (n = 19) were grouped as high fall risk; women with SPPB = 10–12 and 0 reported falls (n = 48) were grouped as low fall risk. Random Forests were trained to classify women into these groups, based upon traditional measures of gait and/or signal-based features extracted from accelerometer data. Eleven models investigated combined feature effects on classification accuracy, using 10-fold cross-validation. The models had an average 73.7% accuracy, 81.1% precision, and 0.706 AUC. The best performing model including triaxial data, cross-correlations, and traditional measures of gait had 78.9% accuracy, 84.4% precision, and 0.846 AUC. Mediolateral signal-based measures—coefficient of variance, cross-correlation with anteroposterior accelerations, and mean acceleration—ranked as the top 3 features. The classification accuracy is promising, given research on probabilistic models of falls indicates accuracies ≥80% are challenging to achieve. The results suggest accelerometer-based measures captured during walking are potentially useful in screening older women for fall risk. We are applying algorithms developed in this paper on an OPACH dataset of 5000 women with a 1-year prospective falls log and week-long, free-living accelerometer data.

A hip-worn device that measures walking motion can help identify which older women are at heightened risk for falling. Andrew Hua, from the University of Illinois at Urbana-Champaign, USA, and colleagues put 67 elderly women through a series of tests to assess their lower extremity function. They also asked the study participants about fall histories in the past year and strapped a triaxial accelerometer to the women’s hips while they completed a 400-meter walking test. Analyses showed that the accelerometry data, when fed into a machine-learning algorithm, were predictive of physical ability and fall risk. Based on these results, the researchers are validating the algorithm in a larger study of 5000 women who wore hip accelerometers for a full week and reported falls prospectively for one-year.

IMU-based gait analysis in lower limb prosthesis users: Comparison of step demarcation algorithms

BACKGROUND

Inertial Measurement Unit (IMU)-based gait analysis algorithms have previously been validated in healthy controls. However, little is known about the efficacy, performance, and applicability of these algorithms in clinical populations with gait deviations such as lower limb prosthesis users (LLPUs).

RESEARCH QUESTION

To compare the performance of 3 different IMU-based algorithms to demarcate steps from LLPUs.

METHODS

We used a single IMU sensor affixed to the midline lumbopelvic region of 17 transtibial (TTA), 16 transfemoral (TFA) LLPUs, and 14 healthy controls (HC). We collected acceleration and angular velocity data during overground walking trials. Step demarcation was evaluated based on fore-aft acceleration, detecting either: (i) maximum acceleration peak, (ii) zero-crossing, or (iii) the peak immediately preceding a zero-crossing. We quantified and compared the variability (standard deviation) in acceleration waveforms from superposed step intervals, and variability in step duration, by each algorithm.

RESULTS

We found that the zero-crossing algorithm outperformed both peak detection algorithms in 65% of TTAs, 81% of TFAs, and 71% of HCs, as evidenced by lower standard deviations in acceleration, more consistent qualitative demarcation of steps, and more normally distributed step durations.

SIGNIFICANCE

The choice of feature-based algorithm with which to partition IMU waveforms into individual steps can affect the quality and interpretation of estimated gait spatiotemporal metrics in LLPUs. We conclude that the fore-aft acceleration zero-crossing serves as a more reliable feature for demarcating steps in the gait patterns of LLPUs.