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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
#1
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
#2
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
#3
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
#4
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
#5
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
#6
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
#7
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
#8
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
https://www.readbyqxmd.com/read/28251444/combining-novelty-detectors-to-improve-accelerometer-based-fall-detection
#9
Carlos Medrano, Raúl Igual, Iván García-Magariño, Inmaculada Plaza, Guillermo Azuara
Research on body-worn sensors has shown how they can be used for the detection of falls in the elderly, which is a relevant health problem. However, most systems are trained with simulated falls, which differ from those of the target population. In this paper, we tackle the problem of fall detection using a combination of novelty detectors. A novelty detector can be trained only with activities of daily life (ADL), which are true movements recorded in real life. In addition, they allow adapting the system to new users, by recording new movements and retraining the system...
March 1, 2017: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/28251357/freezing-of-gait-and-fall-detection-in-parkinson-s-disease-using-wearable-sensors-a-systematic-review
#10
REVIEW
Ana Lígia Silva de Lima, Luc J W Evers, Tim Hahn, Lauren Bataille, Jamie L Hamilton, Max A Little, Yasuyuki Okuma, Bastiaan R Bloem, Marjan J Faber
Despite the large number of studies that have investigated the use of wearable sensors to detect gait disturbances such as Freezing of gait (FOG) and falls, there is little consensus regarding appropriate methodologies for how to optimally apply such devices. Here, an overview of the use of wearable systems to assess FOG and falls in Parkinson's disease (PD) and validation performance is presented. A systematic search in the PubMed and Web of Science databases was performed using a group of concept key words...
March 1, 2017: Journal of Neurology
https://www.readbyqxmd.com/read/28248856/comparison-of-gait-symmetry-between-poststroke-fallers-and-nonfallers-during-level-walking-using-triaxial-accelerometry-a-strobe-compliant-cross-sectional-study
#11
Wei-Chih Lien, Yung-Heng Cheng, Ta-Shen Kuan, Yu-Lun Zheng, Chao-Hsien Hsieh, Wen-Fong Wang
To compare the degree of gait symmetry of chronic poststroke fallers with that of nonfallers during level walking using triaxial accelerometry.In this cross-sectional study, a total of 14 patients with chronic stroke were recruited from a community hospital from February 2015 to July 2016. Patient characteristics, including the number of falls in the previous 12 months, were obtained from medical records. The Berg Balance Scale (BBS) and timed up and go (TUG) test were used at the onset of the study. Triaxial accelerometers were attached to the back and bilateral lower extremities of each subject with sampling rates of 120 Hz...
March 2017: Medicine (Baltimore)
https://www.readbyqxmd.com/read/28227925/principal-component-analysis-can-decrease-neural-networks-performance-for-incipient-falls-detection-a-preliminary-study-with-hands-and-feet-accelerations
#12
Fiorenzo Artoni, Dario Martelli, Vito Monaco, Silvestre Micera, 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/28227635/identifying-the-number-and-location-of-body-worn-sensors-to-accurately-classify-walking-transferring-and-sedentary-activities
#13
Omar Aziz, Stephen N Robinovitch, Edward J Park, Omar Aziz, Stephen N Robinovitch, Edward J Park, Omar Aziz, Edward J Park, Stephen N Robinovitch
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/28227589/uhf-wearable-battery-free-sensor-module-for-activity-and-falling-detection
#14
Nam Trung Dang, Thang Viet Tran, Wan-Young Chung, Nam Trung Dang, Thang Viet Tran, Wan-Young Chung, Thang Viet Tran, Wan-Young Chung, Nam Trung Dang
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/28227321/fall-detection-algorithms-for-real-world-falls-harvested-from-lumbar-sensors-in-the-elderly-population-a-machine-learning-approach
#15
Alan K Bourke, Jochen Klenk, Lars Schwickert, Kamiar Aminian, Espen A F Ihlen, Sabato Mellone, Jorunn L Helbostad, Lorenzo Chiari, Clemens Becker, Alan K Bourke, Jochen Klenk, Lars Schwickert, Kamiar Aminian, Espen A F Ihlen, Sabato Mellone, Jorunn L Helbostad, Lorenzo Chiari, Clemens Becker, Lorenzo Chiari, Lars Schwickert, Kamiar Aminian, Clemens Becker, Jorunn L Helbostad, Jochen Klenk, Alan K Bourke, Sabato Mellone, Espen A F Ihlen
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/28227174/two-threshold-energy-based-fall-detection-using-a-triaxial-accelerometer
#16
Angela Sucerquia, Jose D Lopez, Francisco Vargas, Angela Sucerquia, Jose D Lopez, Francisco Vargas, Angela Sucerquia, Francisco Vargas, Jose D Lopez
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/28226582/towards-holistic-free-living-assessment-in-parkinson-s-disease-unification-of-gait-and-fall-algorithms-with-a-single-accelerometer
#17
Alan Godfrey, Alan Bourke, Silvia Del Din, Rosie Morris, Aodhan Hickey, Jorunn L Helbostad, Lynn Rochester, Alan Godfrey, Alan Bourke, Silvia Del Din, Rosie Morris, Aodhan Hickey, Jorunn L Helbostad, Lynn Rochester, Silvia Del Din, Rosie Morris, Alan Godfrey, Lynn Rochester, Jorunn L Helbostad, Aodhan Hickey, Alan Bourke
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/28208707/gaitkeeper-a-system-for-measuring-canine-gait
#18
Cassim Ladha, Jack O'Sullivan, Zoe Belshaw, Lucy Asher
It is understood gait has the potential to be used as a window into neurodegenerative disorders, identify markers of subclinical pathology, inform diagnostic algorithms of disease progression and measure the efficacy of interventions. Dogs' gaits are frequently assessed in a veterinary setting to detect signs of lameness. Despite this, a reliable, affordable and objective method to assess lameness in dogs is lacking. Most described canine lameness assessments are subjective, unvalidated and at high risk of bias...
February 8, 2017: Sensors
https://www.readbyqxmd.com/read/28207403/predictive-walking-age-health-analyzer
#19
Priyanka Mandal, Krishna Tank, Tapas Monday, Chih-Hung Chen, M Jamal Deen
A simple, low-power and wearable health analyzer for early identification and management of some diseases is presented. To achieve this goal, we propose a walking pattern analysis system that uses features such as speed, energy, turn ratio, and bipedal behavior to characterize and classify individuals in distinct walking-ages. A database is constructed from 74 healthy young adults in the age range of 18 to 60 years using the combination of inertial signals from an accelerometer and a gyroscope on a level path including turns...
February 9, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28193716/preventing-falls-in-a-high-risk-vision-impaired-population-through-specialist-orientation-and-mobility-services-protocol-for-the-platform-randomised-trial
#20
Lisa Keay, Lisa Dillon, Lindy Clemson, Anne Tiedemann, Catherine Sherrington, Peter McCluskey, Pradeep Ramulu, Stephen Jan, Kris Rogers, Jodi Martin, Frances Tinsley, Kirsten Bonrud Jakobsen, Rebecca Q Ivers
BACKGROUND: Older people with vision impairment have significant ongoing morbidity, including risk of falls, but are neglected in fall prevention programmes. PlaTFORM is a pragmatic evaluation of the Lifestyle-integrated Functional Exercise fall prevention programme for older people with vision impairment or blindness (v-LiFE). Implementation and scalability issues will also be investigated. METHODS: PlaTFORM is a single-blinded, randomised trial designed to evaluate the v-LiFE programme compared with usual care...
February 13, 2017: Injury Prevention: Journal of the International Society for Child and Adolescent Injury Prevention
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