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

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6836
Author(s):  
José Gabriel Argañarás ◽  
Yan Tat Wong ◽  
Rezaul Begg ◽  
Nemai Chandra Karmakar
Keyword(s):  
Risk Assessment ◽  
Fall Prevention ◽  
Wearable Sensors ◽  
Machine Learning Algorithms ◽  
Gait Parameters ◽  
Prevention Interventions ◽  
New Applications ◽  
Gait Monitoring ◽  
Application Specific

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

scholarly journals 68 Task Specificity in Fall Prevention

2019 ◽  
Vol 48 (Supplement_4) ◽  
pp. iv18-iv27
Author(s):  
Stephen Lord
Keyword(s):  
Quality Of Life ◽  
Fall Prevention ◽  
Fall Risk ◽  
Wearable Sensors ◽  
Well Being ◽  
Task Specificity ◽  
Loss Of Autonomy ◽  
Prevention Interventions ◽  
Task Training

Abstract Falls pose a major threat to the well-being and quality of life of older people. Falls can result in fractures and other injuries, disability and fear and are can trigger a decline in physical function and loss of autonomy. This presentation with synthesises recent published findings on fall risk and mobility assessments and fall prevention interventions and considers how this field of research may evolve in future, Fall risk topics include the utility of remote monitoring using wearable sensors and recent work investigating brain activation and gait adaptability. New approaches for exercise for fall fall prevention including dual task training, cognitive-motor training with exergames and reactive step training are discussed. The presentation will discuss how these new initiatives and technologies have potential for effective fall prevention and improved quality of life. It concludes by emphasising the need for a continued focus on translation of evidence into practice including robust effectiveness evaluations of so that resources can be appropriately targeted into the future.

scholarly journals 220 Is Multifactorial Risk Assessment a Team Sport? Disciplinary Differences in Perceived Acceptability and Feasibility of a Community-based Fall Prevention Service

2019 ◽  
Vol 48 (Supplement_3) ◽  
pp. iii17-iii65
Author(s):  
Sheena McHugh ◽  
Finola Cronin ◽  
Eileen Moriarty ◽  
Spencer Turvey ◽  
Patrick Barry ◽  
...  
Keyword(s):  
Public Health ◽  
Risk Assessment ◽  
Fall Prevention ◽  
Relative Advantage ◽  
Public Health Nurses ◽  
Multidisciplinary Teams ◽  
Community Based ◽  
Disciplinary Differences ◽  
Falls Risk ◽  
Prevention Interventions

Abstract Background Multifactorial falls risk assessment is an evidence-based practice recommended to prevent falls among older people. Previous research has identified cultural, practical and professional challenges to implementing complex fall prevention interventions. Fall prevention interventions are frequently delivered by multidisciplinary teams (MDTs). This requires multiple health professionals, who practice under different professional norms and governance structures, to accommodate new ways of working. Our aim is to explore disciplinary differences in the perceived acceptability, appropriateness and feasibility of community-based multifactorial falls risk assessment clinics during initial implementation. Methods A mixed methods study is being conducted with analysis of administrative data on delivery of risk assessments (2016-2018), and semi-structured interviews staff involved in multidisciplinary teams (physiotherapists (PT, n=5), occupational therapists (OT, n=6), and public health nurses (n=4)]. Interviews were conducted prior to implementation and at 6 months (n=30 interviews total). Framework-driven thematic analysis was used to identify factors influencing implementation and explore perceptions of acceptability, appropriateness and feasibility. Results Implementation varied across disciplines; 28% of assessments were conducted by nurses (n=83), 36% (n=111) by physiotherapists, and 36% (n=108) by OTs. Preliminary qualitative analysis suggests that OTs welcomed the opportunity to expand their scope of practice. Conducting assessments at set times in static clinics was incompatible with public health nurses’ workflow. Their limited availability and time-sensitive competing priorities were barriers to the feasibility of an MDT-approach. Physiotherapists questioned the relative advantage of a broad assessment, and whether it was an appropriate use of resources given waiting lists for physiotherapy intervention. Data analysis is ongoing. Conclusion The study results have already been used to inform service adaptations including the introduction of dedicated intervention sessions. Training and implementation support for multidisciplinary teams may need to be tailored to the needs of different professional groups to enhance adoption and fidelity.

scholarly journals Automatic gait analysis during steady and unsteady walking using a smartphone

2021 ◽  
Author(s):  
Arshad Sher ◽  
David Langford ◽  
Einar Dogger ◽  
Dan Monaghan ◽  
Luke Ian Lunn ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Gait Analysis ◽  
Monitoring System ◽  
Gait Parameters ◽  
Health Quality ◽  
Health Quality Of Life ◽  
Gait Monitoring ◽  
Walking Aid

How people walk often reveals key insights into health, quality of life and independence. Here, we propose a smartphone-based gait monitoring system which is sensitive and accurate enough to measure temporal gait parameters during unsteady walking, differentiate between normal and impaired gait, and recognise changes in the impaired gait depending on the use of medication or walking aid.

scholarly journals Automatic gait analysis during steady and unsteady walking using a smartphone

2021 ◽  
Author(s):  
Arshad Sher ◽  
David Langford ◽  
Einar Dogger ◽  
Dan Monaghan ◽  
Luke Ian Lunn ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Gait Analysis ◽  
Monitoring System ◽  
Gait Parameters ◽  
Health Quality ◽  
Health Quality Of Life ◽  
Gait Monitoring ◽  
Walking Aid

How people walk often reveals key insights into health, quality of life and independence. Here, we propose a smartphone-based gait monitoring system which is sensitive and accurate enough to measure temporal gait parameters during unsteady walking, differentiate between normal and impaired gait, and recognise changes in the impaired gait depending on the use of medication or walking aid.

scholarly journals Quality of life as an outcome of fall prevention interventions among the aged: a systematic review

2008 ◽  
Vol 19 (1) ◽  
pp. 7-15 ◽  
Author(s):  
S. S. Vaapio ◽  
M. J. Salminen ◽  
A. Ojanlatva ◽  
S.-L. Kivela
Keyword(s):  
Quality Of Life ◽  
Systematic Review ◽  
Fall Prevention ◽  
Prevention Interventions

scholarly journals Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ramon J. Boekesteijn ◽  
José M. H. Smolders ◽  
Vincent J. J. F. Busch ◽  
Alexander C. H. Geurts ◽  
Katrijn Smulders
Keyword(s):  
Dual Task ◽  
Wearable Sensors ◽  
Body Motion ◽  
Effect Sizes ◽  
Upper Body ◽  
Healthy Controls ◽  
Gait Parameters ◽  
Dual Task Cost ◽  
Dual Task Performance ◽  
Spatiotemporal Parameters

Abstract Background Although it is well-established that osteoarthritis (OA) impairs daily-life gait, objective gait assessments are not part of routine clinical evaluation. Wearable inertial sensors provide an easily accessible and fast way to routinely evaluate gait quality in clinical settings. However, during these assessments, more complex and meaningful aspects of daily-life gait, including turning, dual-task performance, and upper body motion, are often overlooked. The aim of this study was therefore to investigate turning, dual-task performance, and upper body motion in individuals with knee or hip OA in addition to more commonly assessed spatiotemporal gait parameters using wearable sensors. Methods Gait was compared between individuals with unilateral knee (n = 25) or hip OA (n = 26) scheduled for joint replacement, and healthy controls (n = 27). For 2 min, participants walked back and forth along a 6-m trajectory making 180° turns, with and without a secondary cognitive task. Gait parameters were collected using 4 inertial measurement units on the feet and trunk. To test if dual-task gait, turning, and upper body motion had added value above spatiotemporal parameters, a factor analysis was conducted. Effect sizes were computed as standardized mean difference between OA groups and healthy controls to identify parameters from these gait domains that were sensitive to knee or hip OA. Results Four independent domains of gait were obtained: speed-spatial, speed-temporal, dual-task cost, and upper body motion. Turning parameters constituted a gait domain together with cadence. From the domains that were obtained, stride length (speed-spatial) and cadence (speed-temporal) had the strongest effect sizes for both knee and hip OA. Upper body motion (lumbar sagittal range of motion), showed a strong effect size when comparing hip OA with healthy controls. Parameters reflecting dual-task cost were not sensitive to knee or hip OA. Conclusions Besides more commonly reported spatiotemporal parameters, only upper body motion provided non-redundant and sensitive parameters representing gait adaptations in individuals with hip OA. Turning parameters were sensitive to knee and hip OA, but were not independent from speed-related gait parameters. Dual-task parameters had limited additional value for evaluating gait in knee and hip OA, although dual-task cost constituted a separate gait domain. Future steps should include testing responsiveness of these gait domains to interventions aiming to improve mobility.

scholarly journals Identifying Fall Risk Predictors by Monitoring Daily Activities at Home Using a Depth Sensor Coupled to Machine Learning Algorithms

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1957
Author(s):  
Amandine Dubois ◽  
Titus Bihl ◽  
Jean-Pierre Bresciani
Keyword(s):  
Machine Learning ◽  
Fall Prevention ◽  
Fall Risk ◽  
Learning Algorithms ◽  
Step Length ◽  
Machine Learning Algorithms ◽  
Daily Activities ◽  
Sitting Time ◽  
Behavioral Parameters ◽  
At Home

Because of population ageing, fall prevention represents a human, economic, and social issue. Currently, fall-risk is assessed infrequently, and usually only after the first fall occurrence. Home monitoring could improve fall prevention. Our aim was to monitor daily activities at home in order to identify the behavioral parameters that best discriminate high fall risk from low fall risk individuals. Microsoft Kinect sensors were placed in the room of 30 patients temporarily residing in a rehabilitation center. The sensors captured the patients’ movements while they were going about their daily activities. Different behavioral parameters, such as speed to sit down, gait speed or total sitting time were extracted and analyzed combining statistical and machine learning algorithms. Our algorithms classified the patients according to their estimated fall risk. The automatic fall risk assessment performed by the algorithms was then benchmarked against fall risk assessments performed by clinicians using the Tinetti test and the Timed Up and Go test. Step length, sit-stand transition and total sitting time were the most discriminant parameters to classify patients according to their fall risk. Coupling step length to the speed required to stand up or the total sitting time gave rise to an error-less classification of the patients, i.e., to the same classification as that of the clinicians. A monitoring system extracting step length and sit-stand transitions at home could complement the clinicians’ assessment toolkit and improve fall prevention.

scholarly journals Robot-Assisted Gait Training in Patients with Multiple Sclerosis: A Randomized Controlled Crossover Trial

Medicina ◽  
2021 ◽  
Vol 57 (7) ◽  
pp. 713
Author(s):  
Cristiano Sconza ◽  
Francesco Negrini ◽  
Berardo Di Matteo ◽  
Alberto Borboni ◽  
Gennaro Boccia ◽  
...  
Keyword(s):  
Crossover Trial ◽  
Gait Training ◽  
Treatment Session ◽  
Control Group ◽  
Walk Test ◽  
Robot Assisted ◽  
Randomized Controlled ◽  
Gait Parameters ◽  
Before And After

Background and Objectives: Gait disorders represent one of the most disabling aspects in multiple sclerosis (MS) that strongly influence patient quality of life. The improvement of walking ability is a primary goal for rehabilitation treatment. The aim of this study is to evaluate the effectiveness of robot-assisted gait training (RAGT) in association with physiotherapy treatment in patients affected by MS in comparison with ground conventional gait training. Study design: Randomized controlled crossover trial. Materials and Methods: Twenty-seven participants affected by MS with EDSS scores between 3.5 and 7 were enrolled, of whom seventeen completed the study. They received five training sessions per week over five weeks of conventional gait training with (experimental group) or without (control group) the inclusion of RAGT. The patients were prospectively evaluated before and after the first treatment session and, after the crossover phase, before and after the second treatment session. The evaluation was based on the 25-foot walk test (25FW, main outcome), 6 min walk test (6MWT), Tinetti Test, Modified Ashworth Scale, and modified Motricity Index for lower limbs. We also measured disability parameters using Functional Independence Measure and Quality of Life Index, and instrumental kinematic and gait parameters: knee extensor strength, double-time support, step length ratio; 17 patients reached the final evaluation. Results: Both groups significantly improved on gait parameters, motor abilities, and autonomy recovery in daily living activities with generally better results of RAGT over control treatment. In particular, the RAGT group improved more than control group in the 25FW (p = 0.004) and the 6MWT (p = 0.022). Conclusions: RAGT is a valid treatment option that in association with physiotherapy could induce positive effects in MS-correlated gait disorders. Our results showed greater effectiveness in recovering gait speed and resistance than conventional gait training.

scholarly journals Late-Maturity Alpha-Amylase in Wheat (Triticum aestivum) and Its Impact on Fresh White Sauce Qualities

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 201
Author(s):  
Galex K. S. Neoh ◽  
Mark J. Dieters ◽  
Keyu Tao ◽  
Glen P. Fox ◽  
Phuong T. M. Nguyen ◽  
...  
Keyword(s):  
Grain Filling ◽  
Drastic Reduction ◽  
Product Usage ◽  
Low Viscosity ◽  
Pasting Characteristics ◽  
Late Maturity ◽  
Semi Solid ◽  
New Applications ◽  
White Sauce

When wheat experiences a cold-temperature ‘shock’ during the late stage of grain filling, it triggers the abnormal synthesis of late-maturity α-amylase (LMA). This increases the enzyme content in affected grain, which can lead to a drastic reduction in falling number (FN). By commercial standards, a low FN is taken as an indication of inferior quality, deemed unsuitable for end-product usage. Hence, LMA-affected grains are either rejected or downgraded to feed grade at the grain receiving point. However, previous studies have found no substantial correlation between low FN-LMA and bread quality. The present study extends previous investigations to semi-solid food, evaluating the physical quality of fresh white sauce processed from LMA-affected flour. Results show that high-LMA flours had low FNs and exhibited poor pasting characteristics. However, gelation occurred in the presence of other components during fresh white sauce processing. This demonstrates that LMA-affected flours may have new applications in low-viscosity products.

scholarly journals Influence of End Mill Manufacturing on Cutting Edge Quality and Wear Behavior

2021 ◽  
Vol 5 (3) ◽  
pp. 77
Author(s):  
Berend Denkena ◽  
Alexander Krödel-Worbes ◽  
Sascha Beblein ◽  
Markus Hein
Keyword(s):  
Wear Behavior ◽  
Cutting Edge ◽  
End Mills ◽  
Edge Quality ◽  
Manufacturing Process Chain ◽  
The Individual ◽  
Application Specific ◽  
Milling Tools ◽  
Edge Preparation

One of the decisive factors for the performance of milling tools is the quality of the cutting edge. The latter results from the process control of the individual steps along the tool manufacturing process chain, which generally includes the sintering or pressing of the blanks, grinding, cutting edge preparation, and coating of the tools. However, the targeted and application-specific design of the process steps in terms of high economic efficiency is currently limited by a lack of knowledge regarding the influence of the corresponding process parameters on the resulting cutting edge quality. In addition, there is a lack of suitable parameters that adequately represent the characteristics of the cutting edge microtopography. This publication therefore investigates the influence of manufacturing processes on cutting edge quality and wear behavior of end mills. On this basis, different characterization parameters for the cutting edge quality are derived and evaluated with regard to their ability to predict the wear behavior.

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