Development of a standard fall data format for signals from body-worn sensors

No abstract is available for this paper.

• Publication year

  2013

• Venue

  Zeitschrift für Gerontologie und Geriatrie (Print)

• Publication date

  2013-11-24

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1007/s00391-013-0554-0PMID 24271252
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Video capture of the circumstances of falls in elderly people residing in long-term care: an observational study.

  2013cited by this paper
• What videos can tell us about falling.

  2013cited by this paper
• Fall detection with body-worn sensors

  2013cited by this paper
• Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls

  2012cited by this paper
• Epidemiology of falls in residential aged care: analysis of more than 70,000 falls from residents of bavarian nursing homes.

  2012cited by this paper
• Prevalence of psychotropic medication use among German and Austrian nursing home residents: a comparison of 3 cohorts.

  2012cited by this paper
• Comparison of real-life accidental falls in older people with experimental falls in middle-aged test subjects.

  2012cited by this paper
• Feasibility and accuracy of fall reports in persons with dementia: a prospective observational study

  2011cited by this paper
• Comparison of acceleration signals of simulated and real-world backward falls.

  2011cited by this paper
• Fall algorithm development using kinematic parameters measured from simulated falls performed in a quasi-realistic environment using accelerometry

  2011cited by this paper
• Utilization of the Seniors Falls Investigation Methodology to identify system-wide causes of falls in community-dwelling seniors.

  2009cited by this paper
• Wearable systems for monitoring mobility-related activities in older people: a systematic review

  2008cited by this paper
• Falls in older people: epidemiology, risk factors and strategies for prevention.

  2006cited by this paper
• Development of a Common Outcome Data Set for Fall Injury Prevention Trials: The Prevention of Falls Network Europe Consensus

  2005cited by this paper
• Accuracy Of Patient Recall And Chart Documentation Of Falls

  1993cited by this paper

• Exploring the Landscape of Standards and Guidelines in AgeTech Design and Development: Scoping Review and Thematic Analysis

  2024cites this paper
• Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization

  2023cites this paper
• Contactless Fall Detection for the Elderly

  2021cites this paper
• Wie assistive Technologien intergenerationelle Beziehungen mitgestalten: kulturgerontologische Perspektiven

  2021cites this paper
• Accelerometer-Based Fall Detection Using Machine Learning: Training and Testing on Real-World Falls

  2020cites this paper
• A Novel Dual-Task Balance Challenge to Prevent Falls in Older Adults: A Randomized Pilot Study

  2019cites this paper
• Pertinence et implications de l’actimétrie en réadaptation

  2019cites this paper
• Rilevanza e implicazioni dell’actimetria in riabilitazione

  2019cites this paper
• Pertinencia e implicaciones de la actimetría en rehabilitación

  2019cites this paper
• Risk of traumatic intracranial haemorrhage is increased in older people exposed to oral anticoagulation with phenprocoumon

  2019cites this paper
• Fall detection monitoring systems: a comprehensive review

  2018cites this paper
• Methods for the Real-World Evaluation of Fall Detection Technology: A Scoping Review

  2018cites this paper
• A Physical Activity Reference Data-Set Recorded from Older Adults Using Body-Worn Inertial Sensors and Video Technology—The ADAPT Study Data-Set

  2017cites this paper
• The influence of dementia on falls, gait and rehabilitation

  2017cites this paper
• Prävention von Stürzen und sturzbedingten Verletzungen

  2017cites this paper
• Fall detection algorithms for real-world falls harvested from lumbar sensors in the elderly population: a machine learning approach.

  2016cites this paper
• Fall detection algorithms for real-world falls harvested from lumbar sensors in the elderly population: A machine learning approach

  2016cites this paper
• Review of how we should define (and measure) adherence in studies examining older adults' participation in exercise classes

  2016cites this paper
• The FARSEEING real-world fall repository: a large-scale collaborative database to collect and share sensor signals from real-world falls

  2016cites this paper
• Falls risk assessment for hospitalised older adults: a combination of motion data and vital signs

  2016cites this paper
• The Risk of Hospital Admission Due to Traumatic Brain Injury Is Increased in Older Persons With Severe Functional Limitations.

  2016cites this paper
• Analysis of Android Device-Based Solutions for Fall Detection

  2015cites this paper
• A comparison of public datasets for acceleration-based fall detection.

  2015cites this paper
• UWB-radar monitoring of movements in homes of elderly and disabled people — An interdisciplinary perspective (RADCARE)

  2015cites this paper
• Falls in older community-dwelling women and men : risk factors and safety strategies. Fall risk awareness, fear of falling, and preferred exercise properties from a gender perspective.

  2015cites this paper
• Video Analysis of the Circumstances of Falls in Long-term Care

  2015cites this paper
• Agreement between video footage and fall incident reports on the circumstances of falls in long-term care.

  2015cites this paper
• An investigation of clinical and sensor-based fall-risk assessment in community-dwelling older adults

  2014cites this paper
• Detecting Falls as Novelties in Acceleration Patterns Acquired with Smartphones

  2014cites this paper
• Comparison and Characterization of Android-Based Fall Detection Systems

  2014cites this paper
• What Does Big Data Mean for Wearable Sensor Systems?

  2014cites this paper