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https://www.readbyqxmd.com/read/28590432/faller-classification-in-older-adults-using-wearable-sensors-based-on-turn-and-straight-walking-accelerometer-based-features
#1
Dylan Drover, Jennifer Howcroft, Jonathan Kofman, Edward D Lemaire
Faller classification in elderly populations can facilitate preventative care before a fall occurs. A novel wearable-sensor based faller classification method for the elderly was developed using accelerometer-based features from straight walking and turns. Seventy-six older individuals (74.15 ± 7.0 years), categorized as prospective fallers and non-fallers, completed a six-minute walk test with accelerometers attached to their lower legs and pelvis. After segmenting straight and turn sections, cross validation tests were conducted on straight and turn walking features to assess classification performance...
June 7, 2017: Sensors
https://www.readbyqxmd.com/read/28559455/association-between-childcare-educators-practices-and-preschoolers-physical-activity-and-dietary-intake-a-cross-sectional-analysis
#2
Stéphanie Ward, Mathieu Blanger, Denise Donovan, Hassan Vatanparast, Nazeem Muhajarine, Rachel Engler-Stringer, Anne Leis, M Louise Humbert, Natalie Carrier
INTRODUCTION: Childcare educators may be role models for healthy eating and physical activity (PA) behaviours among young children. This study aimed to identify which childcare educators' practices are associated with preschoolers' dietary intake and PA levels. METHODS: This cross-sectional analysis included 723 preschoolers from 50 randomly selected childcare centres in two Canadian provinces. All data were collected in the fall of 2013 and 2014 and analysed in the fall of 2015...
May 30, 2017: BMJ Open
https://www.readbyqxmd.com/read/28558724/feature-selection-for-elderly-faller-classification-based-on-wearable%C3%A2-sensors
#3
Jennifer Howcroft, Jonathan Kofman, Edward D Lemaire
BACKGROUND: Wearable sensors can be used to derive numerous gait pattern features for elderly fall risk and faller classification; however, an appropriate feature set is required to avoid high computational costs and the inclusion of irrelevant features. The objectives of this study were to identify and evaluate smaller feature sets for faller classification from large feature sets derived from wearable accelerometer and pressure-sensing insole gait data. METHODS: A convenience sample of 100 older adults (75...
May 30, 2017: Journal of Neuroengineering and Rehabilitation
https://www.readbyqxmd.com/read/28552947/relationship-of-mechanical-impact-magnitude-to-neurologic-dysfunction-severity-in-a-rat-traumatic-brain-injury-model
#4
Tsung-Hsun Hsieh, Jing-Wei Kang, Jing-Huei Lai, Ying-Zu Huang, Alexander Rotenberg, Kai-Yun Chen, Jia-Yi Wang, Shu-Yen Chan, Shih-Ching Chen, Yung-Hsiao Chiang, Chih-Wei Peng
OBJECTIVE: Traumatic brain injury (TBI) is a major brain injury type commonly caused by traffic accidents, falls, violence, or sports injuries. To obtain mechanistic insights about TBI, experimental animal models such as weight-drop-induced TBI in rats have been developed to mimic closed-head injury in humans. However, the relationship between the mechanical impact level and neurological severity following weight-drop-induced TBI remains uncertain. In this study, we comprehensively investigated the relationship between physical impact and graded severity at various weight-drop heights...
2017: PloS One
https://www.readbyqxmd.com/read/28509870/sound-power-estimation-for-beam-and-plate-structures-using-polyvinylidene-fluoride-films-as-sensors
#5
Qibo Mao, Haibing Zhong
The theory for calculation and/or measurement of sound power based on the classical velocity-based radiation mode (V-mode) approach is well established for planar structures. However, the current V-mode theory is limited in scope in that it can only be applied to conventional motion sensors (i.e., accelerometers). In this study, in order to estimate the sound power of vibrating beam and plate structure by using polyvinylidene fluoride (PVDF) films as sensors, a PVDF-based radiation mode (C-mode) approach concept is introduced to determine the sound power radiation from the output signals of PVDF films of the vibrating structure...
May 16, 2017: Sensors
https://www.readbyqxmd.com/read/28475196/do-clinical-assessments-steady-state-or-daily-life-gait-characteristics-predict-falls-in-ambulatory-chronic-stroke-survivors
#6
Michiel Punt, Sjoerd M Bruijn, Harriet Wittink, Ingrid G van de Port, Jaap H van Dieën
OBJECTIVE: This exploratory study investigated to what extent gait characteristics and clinical physical therapy assessments predict falls in chronic stroke survivors. DESIGN: Prospective study. SUBJECTS: Chronic fall-prone and non-fall-prone stroke survivors. METHODS: Steady-state gait characteristics were collected from 40 participants while walking on a treadmill with motion capture of spatio-temporal, variability, and stability measures...
May 5, 2017: Journal of Rehabilitation Medicine
https://www.readbyqxmd.com/read/28461079/-reproducibility-of-quantifying-timed-up-and-go-test-measured-with-smartphone-accelerometers-in-older-people-living-in-the-community
#7
Jorge Campillay Guzmán, Ricardo Guzmán Silva, Rodrigo Guzmán-Venegas
INTRODUCTION: Inertial Measurement Units (IMU) incorporated in smartphones can provide records that match registers obtained by laboratory instruments. This means that the use of smartphones would be feasible for recording three-dimensional kinematics parameters like velocity and acceleration, enabling more robust analyses, such as the Timed Up and Go (TUG) test, that assess the risk of falls older people (OP) living in the community. METHOD: The study included 35 female OP, users of the Family Health Centres (CESFAM) Juan Pablo II and Corvallis from Antofagasta city, Chile...
April 28, 2017: Revista Española de Geriatría y Gerontología
https://www.readbyqxmd.com/read/28448509/better-than-counting-seconds-identifying-fallers-among-healthy-elderly-using-fusion-of-accelerometer-features-and-dual-task-timed-up-and-go
#8
Moacir Ponti, Patricia Bet, Caroline L Oliveira, Paula C Castro
Devices and sensors for identification of fallers can be used to implement actions to prevent falls and to allow the elderly to live an independent life while reducing the long-term care costs. In this study we aimed to investigate the accuracy of Timed Up and Go test, for fallers' identification, using fusion of features extracted from accelerometer data. Single and dual tasks TUG (manual and cognitive) were performed by a final sample (94% power) of 36 community dwelling healthy older persons (18 fallers paired with 18 non-fallers) while they wear a single triaxial accelerometer at waist with sampling rate of 200Hz...
2017: PloS One
https://www.readbyqxmd.com/read/28443059/algorithm-for-turning-detection-and-analysis-validated-under-home-like-conditions-in-patients-with-parkinson-s-disease-and-older-adults-using-a-6-degree-of-freedom-inertial-measurement-unit-at-the-lower-back
#9
Minh H Pham, Morad Elshehabi, Linda Haertner, Tanja Heger, Markus A Hobert, Gert S Faber, Dina Salkovic, Joaquim J Ferreira, Daniela Berg, Álvaro Sanchez-Ferro, Jaap H van Dieën, Walter Maetzler
INTRODUCTION: Aging and age-associated disorders such as Parkinson's disease (PD) are often associated with turning difficulties, which can lead to falls and fractures. Valid assessment of turning and turning deficits specifically in non-standardized environments may foster specific treatment and prevention of consequences. METHODS: Relative orientation, obtained from 3D-accelerometer and 3D-gyroscope data of a sensor worn at the lower back, was used to develop an algorithm for turning detection and qualitative analysis in PD patients and controls in non-standardized environments...
2017: Frontiers in Neurology
https://www.readbyqxmd.com/read/28432935/accelerometry-based-assessment-and-detection-of-early-signs-of-balance-deficits
#10
Heidi Similä, Milla Immonen, Miikka Ermes
Falls are the cause for more than half of the injury-related hospitalizations among older people. Accurate assessment of individuals' fall risk could enable targeted interventions to reduce the risk. This paper presents a novel method for using wearable accelerometers to detect early signs of deficits in balance from gait. Gait acceleration data were analyzed from 35 healthy female participants (73.86±5.40 years). The data were collected with waist-mounted accelerometer and the participants performed three supervised balance tests: Berg Balance Scale (BBS), Timed-Up-and-Go (TUG) and 4m walk...
April 13, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28415071/lower-physical-activity-in-persons-with-multiple-sclerosis-at-increased-fall-risk-a-cross-sectional-study
#11
Emerson Sebastião, Yvonne C Learmonth, Robert W Motl
Persons with multiple sclerosis (MS) often report being afraid of falling, and this may have effects on physical activity (PA) engagement. This study investigated PA levels in persons with MS as a function of fall risk categories. Forty-seven persons with MS participated in the study and were categorized into either increased fall risk (IFR; n = 21; 55.5 ± 9.0 years) or normal fall risk (NFR; n = 26; 51.2 ± 12.9 years) groups based on scores from the Activities-Balance Confidence scale. PA was measured by accelerometer and expressed as average steps per day, and time spent in sedentary behavior, light PA, and moderate to vigorous physical activity over the course of 7 consecutive days...
May 2017: American Journal of Physical Medicine & Rehabilitation
https://www.readbyqxmd.com/read/28358689/prospective-fall-risk-prediction-models-for-older-adults-based-on-wearable-sensors
#12
Jennifer Howcroft, Jonathan Kofman, Edward Lemaire
Wearable sensors can provide quantitative, gait-based assessments that can translate to point-of-care environments. This investigation generated elderly fall-risk predictive models based on wearable-sensor-derived gait data and prospective fall occurrence; and identified the optimal sensor type, location, and combination for single and dual-task walking. 75 individuals who reported six month prospective fall occurrence (75.2 ± 6.6 years; 47 non-fallers, 28 fallers) walked 7.62 m under single-task and dual-task conditions while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, and left and right shanks...
March 24, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28291838/level-and-correlates-of-physical-activity-and-sedentary-behavior-in-patients-with-type-2-diabetes-a-cross-sectional-analysis-of-the-italian-diabetes-and-exercise-study_2
#13
Stefano Balducci, Valeria D'Errico, Jonida Haxhi, Massimo Sacchetti, Giorgio Orlando, Patrizia Cardelli, Nicolina Di Biase, Lucilla Bollanti, Francesco Conti, Silvano Zanuso, Antonio Nicolucci, Giuseppe Pugliese
OBJECTIVE: Patients with type 2 diabetes usually show reduced physical activity (PA) and increased sedentary (SED)-time, though to a varying extent, especially for low-intensity PA (LPA), a major determinant of daily energy expenditure that is not accurately captured by questionnaires. This study assessed the level and correlates of PA and SED-time in patients from the Italian Diabetes and Exercise Study_2 (IDES_2). METHODS: Three-hundred physically inactive and sedentary patients with type 2 diabetes were enrolled in the IDES_2 to be randomized to an intervention group, receiving theoretical and practical exercise counseling, and a control group, receiving standard care...
2017: PloS One
https://www.readbyqxmd.com/read/28269666/principal-component-analysis-can-decrease-neural-networks-performance-for-incipient-falls-detection-a-preliminary-study-with-hands-and-feet-accelerations
#14
Fiorenzo Artoni, Dario Martelli, Vito Monaco, Silvestre Micera
Fall-related accidents constitute a major problem for elderly people and a burden to the health-care national system. It is therefore important to design devices (e.g., accelerometers) and machine learning algorithms able to recognize incipient falls as quickly and reliably as possible. Blind source separation (BSS) methods are often used as a preprocessing step before classification, however the effects of BSS on classification performance are not well understood. The aim of this work is to preliminarily characterize the effect that two methods, namely Principal and Independent Component Analysis (PCA and ICA) and their combined use have on the performance of a neural network in detecting incipient falls...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269392/identifying-the-number-and-location-of-body-worn-sensors-to-accurately-classify-walking-transferring-and-sedentary-activities
#15
Omar Aziz, Stephen N Robinovitch, Edward J Park
In order to perform fall risk assessments using wearable inertial sensors in older adults in their natural settings where falls are likely to occur, a first step is to automatically segment and classify sensor signals of human movements into the known `activities of interest'. Sensor data from such activities can later be used through quantitative and qualitative analysis for differentiating fallers from non-fallers. In this study, ten young adults participated in experimental trials involving several variations of walking, transferring and sedentary activities...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269347/uhf-wearable-battery-free-sensor-module-for-activity-and-falling-detection
#16
Nam Trung Dang, Thang Viet Tran, Wan-Young Chung
Falling is one of the most serious medical and social problems in aging population. Therefore taking care of the elderly by detecting activity and falling for preventing and mitigating the injuries caused by falls needs to be concerned. This study proposes a wearable, wireless, battery free ultra-high frequency (UHF) smart sensor tag module for falling and activity detection. The proposed tag is powered by UHF RF wave from reader and read by a standard UHF Electronic Product Code (EPC) Class-1 Generation-2 reader...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269098/fall-detection-algorithms-for-real-world-falls-harvested-from-lumbar-sensors-in-the-elderly-population-a-machine-learning-approach
#17
Alan K Bourke, Jochen Klenk, Lars Schwickert, Kamiar Aminian, Espen A F Ihlen, Sabato Mellone, Jorunn L Helbostad, Lorenzo Chiari, Clemens Becker
Automatic fall detection will promote independent living and reduce the consequences of falls in the elderly by ensuring people can confidently live safely at home for linger. In laboratory studies inertial sensor technology has been shown capable of distinguishing falls from normal activities. However less than 7% of fall-detection algorithm studies have used fall data recorded from elderly people in real life. The FARSEEING project has compiled a database of real life falls from elderly people, to gain new knowledge about fall events and to develop fall detection algorithms to combat the problems associated with falls...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268967/two-threshold-energy-based-fall-detection-using-a-triaxial-accelerometer
#18
Angela Sucerquia, Jose D Lopez, Francisco Vargas
Elderly fall detection based on accelerometers is an active research area. Nowadays authors are addressing specific problems such as failure rates and energy consumption, but in most cases their strategies do not conciliate these objectives. In this paper we propose a double threshold based methodology with two novel detection features, a product between the sum vector magnitude and the signal magnitude area, and a normalization of the signal magnitude area over five 1 s windows. The methodology was validated using the public Mobifall dataset, and one developed for this work...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268412/towards-holistic-free-living-assessment-in-parkinson-s-disease-unification-of-gait-and-fall-algorithms-with-a-single-accelerometer
#19
Alan Godfrey, Alan Bourke, Silvia Del Din, Rosie Morris, Aodhan Hickey, Jorunn L Helbostad, Lynn Rochester
Technological developments have seen the miniaturization of sensors, small enough to be embedded in wearable devices facilitating unobtrusive and longitudinal monitoring in free-living environments. Concurrently, the advances in algorithms have been ad-hoc and fragmented. To advance the mainstream use of wearable technology and improved functionality of algorithms all methodologies must be unified and robustly tested within controlled and free-living conditions. Here we present and unify a (i) gait segmentation and analysis algorithm and (ii) a fall detection algorithm...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28263256/factors-associated-with-ambulatory-activity-in-de-novo-parkinson-disease
#20
RANDOMIZED CONTROLLED TRIAL
Cory Christiansen, Charity Moore, Margaret Schenkman, Benzi Kluger, Wendy Kohrt, Anthony Delitto, Brian Berman, Deborah Hall, Deborah Josbeno, Cynthia Poon, Julie Robichaud, Toby Wellington, Samay Jain, Cynthia Comella, Daniel Corcos, Ed Melanson
BACKGROUND AND PURPOSE: Objective ambulatory activity during daily living has not been characterized for people with Parkinson disease prior to initiation of dopaminergic medication. Our goal was to characterize ambulatory activity based on average daily step count and examine determinants of step count in nonexercising people with de novo Parkinson disease. METHODS: We analyzed baseline data from a randomized controlled trial, which excluded people performing regular endurance exercise...
April 2017: Journal of Neurologic Physical Therapy: JNPT
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