scholarly journals Hobbit: Providing Fall Detection and Prevention for the Elderly in the Real World

2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
Markus Bajones ◽  
David Fischinger ◽  
Astrid Weiss ◽  
Daniel Wolf ◽  
Markus Vincze ◽  
...  
Keyword(s):  
Real World ◽  
Independent Living ◽  
Low Cost ◽  
Fall Detection ◽  
The Elderly ◽  
Field Trials ◽  
Lessons Learned ◽  
Human Robot Interaction ◽  
Service Robot ◽  
Emergency Situations

We present the robot developed within the Hobbit project, a socially assistive service robot aiming at the challenge of enabling prolonged independent living of elderly people in their own homes. We present the second prototype (Hobbit PT2) in terms of hardware and functionality improvements following first user studies. Our main contribution lies within the description of all components developed within the Hobbit project, leading to autonomous operation of 371 days during field trials in Austria, Greece, and Sweden. In these field trials, we studied how 18 elderly users (aged 75 years and older) lived with the autonomously interacting service robot over multiple weeks. To the best of our knowledge, this is the first time a multifunctional, low-cost service robot equipped with a manipulator was studied and evaluated for several weeks under real-world conditions. We show that Hobbit’s adaptive approach towards the user increasingly eased the interaction between the users and Hobbit. We provide lessons learned regarding the need for adaptive behavior coordination, support during emergency situations, and clear communication of robotic actions and their consequences for fellow researchers who are developing an autonomous, low-cost service robot designed to interact with their users in domestic contexts. Our trials show the necessity to move out into actual user homes, as only there can we encounter issues such as misinterpretation of actions during unscripted human-robot interaction.

scholarly journals A Feasibility Study of the Use of Smartwatches in Wearable Fall Detection Systems

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2254
Author(s):  
Francisco Javier González-Cañete ◽  
Eduardo Casilari
Keyword(s):  
Low Cost ◽  
Fall Detection ◽  
The Elderly ◽  
Point Of View ◽  
False Alarms ◽  
Battery Life ◽  
Area Network ◽  
Battery Lifetime ◽  
Detection Systems ◽  
Operational Aspects

Over the last few years, the use of smartwatches in automatic Fall Detection Systems (FDSs) has aroused great interest in the research of new wearable telemonitoring systems for the elderly. In contrast with other approaches to the problem of fall detection, smartwatch-based FDSs can benefit from the widespread acceptance, ergonomics, low cost, networking interfaces, and sensors that these devices provide. However, the scientific literature has shown that, due to the freedom of movement of the arms, the wrist is usually not the most appropriate position to unambiguously characterize the dynamics of the human body during falls, as many conventional activities of daily living that involve a vigorous motion of the hands may be easily misinterpreted as falls. As also stated by the literature, sensor-fusion and multi-point measurements are required to define a robust and reliable method for a wearable FDS. Thus, to avoid false alarms, it may be necessary to combine the analysis of the signals captured by the smartwatch with those collected by some other low-power sensor placed at a point closer to the body’s center of gravity (e.g., on the waist). Under this architecture of Body Area Network (BAN), these external sensing nodes must be wirelessly connected to the smartwatch to transmit their measurements. Nonetheless, the deployment of this networking solution, in which the smartwatch is in charge of processing the sensed data and generating the alarm in case of detecting a fall, may severely impact on the performance of the wearable. Unlike many other works (which often neglect the operational aspects of real fall detectors), this paper analyzes the actual feasibility of putting into effect a BAN intended for fall detection on present commercial smartwatches. In particular, the study is focused on evaluating the reduction of the battery life may cause in the watch that works as the core of the BAN. To this end, we thoroughly assess the energy drain in a prototype of an FDS consisting of a smartwatch and several external Bluetooth-enabled sensing units. In order to identify those scenarios in which the use of the smartwatch could be viable from a practical point of view, the testbed is studied with diverse commercial devices and under different configurations of those elements that may significantly hamper the battery lifetime.

scholarly journals Re-Enactment as a Method to Reproduce Real-World Fall Events Using Inertial Sensor Data: Development and Usability Study

10.2196/13961 ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. e13961
Author(s):  
Kim Sarah Sczuka ◽  
Lars Schwickert ◽  
Clemens Becker ◽  
Jochen Klenk
Keyword(s):  
Real World ◽  
Independent Living ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Center Of Mass ◽  
Fall Detection ◽  
Video Data ◽  
Sensor Data ◽  
Movement Behavior ◽  
The Real

Background Falls are a common health problem, which in the worst cases can lead to death. To develop reliable fall detection algorithms as well as suitable prevention interventions, it is important to understand circumstances and characteristics of real-world fall events. Although falls are common, they are seldom observed, and reports are often biased. Wearable inertial sensors provide an objective approach to capture real-world fall signals. However, it is difficult to directly derive visualization and interpretation of body movements from the fall signals, and corresponding video data is rarely available. Objective The re-enactment method uses available information from inertial sensors to simulate fall events, replicate the data, validate the simulation, and thereby enable a more precise description of the fall event. The aim of this paper is to describe this method and demonstrate the validity of the re-enactment approach. Methods Real-world fall data, measured by inertial sensors attached to the lower back, were selected from the Fall Repository for the Design of Smart and Self-Adaptive Environments Prolonging Independent Living (FARSEEING) database. We focused on well-described fall events such as stumbling to be re-enacted under safe conditions in a laboratory setting. For the purposes of exemplification, we selected the acceleration signal of one fall event to establish a detailed simulation protocol based on identified postures and trunk movement sequences. The subsequent re-enactment experiments were recorded with comparable inertial sensor configurations as well as synchronized video cameras to analyze the movement behavior in detail. The re-enacted sensor signals were then compared with the real-world signals to adapt the protocol and repeat the re-enactment method if necessary. The similarity between the simulated and the real-world fall signals was analyzed with a dynamic time warping algorithm, which enables the comparison of two temporal sequences varying in speed and timing. Results A fall example from the FARSEEING database was used to show the feasibility of producing a similar sensor signal with the re-enactment method. Although fall events were heterogeneous concerning chronological sequence and curve progression, it was possible to reproduce a good approximation of the motion of a person’s center of mass during fall events based on the available sensor information. Conclusions Re-enactment is a promising method to understand and visualize the biomechanics of inertial sensor-recorded real-world falls when performed in a suitable setup, especially if video data is not available.

Designing Smart Home Environments for Unobtrusive Monitoring for Independent Living

2016 ◽  
Vol 8 (1) ◽  
pp. 47-63 ◽  
Author(s):  
Homer Papadopoulos
Keyword(s):  
Elderly People ◽  
Research Methodology ◽  
Independent Living ◽  
Design Science ◽  
Low Cost ◽  
Science Research ◽  
The Elderly ◽  
Design Science Research ◽  
Integrated System ◽  
Design Science Research Methodology

The “Unobtrusive Smart Environments for Independent Living” EU funded project is proposing an integrated system (USEFIL system) which intends to cope with ageing problem providing advanced, affordable and unobtrusive monitoring and web communication solutions for seniors living independently. The USEFIL system enhances social care and medical service provision by exploiting “frugal” ICT solutions such as low cost “off-the-shelf” technology and unobtrusive monitoring technologies to develop services that will assist the elderly in maintaining their independence throughout their daily activities. The project adopted the Design Science Research Methodology (DSRM) to design and develop the USEFIL system because this methodology incorporates all those principles, practices, and procedures to help us meet USEFIL systems' objectives. Aim of the paper is to demonstrate the use of the DSRM process to design an ICT solution for the case study of ICT technologies for assistive living environments for elderly people. More specifically using the theoretical lens of the Design Science Research Methodology theory the paper presents the necessary steps that have been conducted to design the USEFIL system. The USEFIL system was implemented and validated over a three year period with elderly people, their unofficial carers and doctors. Results demonstrate that the technology readily succeeds in meeting the study's initial objectives. Although the project is still running and the design specification of the USEFIL system is under continuous update, the main modules that have been designed and realized will be presented in the paper.

Integrative Geriatric Medicine

2018 ◽  
Author(s):  
Andrew Weil
Keyword(s):  
Independent Living ◽  
Low Cost ◽  
Geriatric Medicine ◽  
Healthcare Providers ◽  
The Elderly ◽  
Patient Centered ◽  
Geriatric Population ◽  
Care Of Elderly ◽  
Standard Practices ◽  
Outpatient Settings

This book is a detailed, evidence-based reference on the field of integrative geriatric medicine. It is intended for all healthcare providers and advocates who work with the geriatric population—in outpatient settings and nursing homes, assisted and independent living facilities, and senior community centers. In addition, it will provide valuable information for leaders and politicians who are involved with implementing policies and procedures for the care of elderly patients and who are looking for safer, less costly, and more patient-centered approaches. Integrative geriatrics is a new field of medicine that advocates for a whole-person, patient-centered, primarily non-pharmacological approach to medical care of the elderly. Most current geriatric practices overprescribe medications and procedures and underutilize non-pharmacological, low-cost, high-touch methods. Patients, however, often show reluctance toward these standard practices because they often involve invasive interventions. The practice of integrative geriatrics is rooted in lifestyle interventions, such as nutrition, movement therapies, and mind-body and spirituality approaches, that allow patients to take a different path to their health, one that utilizes pharmaceuticals and invasive procedures only when safer integrative approaches are not available or not effective.

Low Cost System for Fall Detection in the Elderly

2020 ◽  
Author(s):  
Tatiana Pereira Filgueiras ◽  
Caroline Ruella Paiva Torres ◽  
Pedro Bertemes Filho
Keyword(s):  
Low Cost ◽  
Fall Detection ◽  
The Elderly ◽  
Cost System

scholarly journals CHARMIE: A Collaborative Healthcare and Home Service and Assistant Robot for Elderly Care

2021 ◽  
Vol 11 (16) ◽  
pp. 7248
Author(s):  
Tiago Ribeiro ◽  
Fernando Gonçalves ◽  
Inês S. Garcia ◽  
Gil Lopes ◽  
António F. Ribeiro
Keyword(s):  
Elderly Care ◽  
Fall Detection ◽  
The Elderly ◽  
Obstacle Detection ◽  
Human Robot Interaction ◽  
Map Building ◽  
Healthcare Facilities ◽  
Assistive Robots ◽  
Wide Range ◽  
Set Up

The global population is ageing at an unprecedented rate. With changes in life expectancy across the world, three major issues arise: an increasing proportion of senior citizens; cognitive and physical problems progressively affecting the elderly; and a growing number of single-person households. The available data proves the ever-increasing necessity for efficient elderly care solutions such as healthcare service and assistive robots. Additionally, such robotic solutions provide safe healthcare assistance in public health emergencies such as the SARS-CoV-2 virus (COVID-19). CHARMIE is an anthropomorphic collaborative healthcare and domestic assistant robot capable of performing generic service tasks in non-standardised healthcare and domestic environment settings. The combination of its hardware and software solutions demonstrates map building and self-localisation, safe navigation through dynamic obstacle detection and avoidance, different human-robot interaction systems, speech and hearing, pose/gesture estimation and household object manipulation. Moreover, CHARMIE performs end-to-end chores in nursing homes, domestic houses, and healthcare facilities. Some examples of these chores are to help users transport items, fall detection, tidying up rooms, user following, and set up a table. The robot can perform a wide range of chores, either independently or collaboratively. CHARMIE provides a generic robotic solution such that older people can live longer, more independent, and healthier lives.

Energy Saving in Forward Fall Detection using Mobile Accelerometer

2013 ◽  
Vol 4 (1) ◽  
pp. 78-94 ◽  
Author(s):  
Vo Quang Viet ◽  
Ali Fahmi Perwira Negera ◽  
Hoang Minh Thang ◽  
Deokjai Choi
Keyword(s):  
Mobile Phone ◽  
Independent Living ◽  
Dynamic Time Warping ◽  
Fall Detection ◽  
Well Being ◽  
The Elderly ◽  
Time Warping ◽  
Save Energy ◽  
Dynamic Time ◽  
Health And Well Being

Fall injury is one of the biggest risks to health and well-being of the elderly especially in independent living because falling accidents may cause instant death. There are many research interests aimed to detect fall incidents. Fall detection is envisioned critical on ICT-assisted healthcare future. In addition, mobile battery is currently another serious problem in which performance feasibility is considered as a standard to verify an effective method. In this paper, the authors study forward fall detection method from mobile phone perspective using accelerometer only without sacrificing accuracy to save energy. Using peak threshold algorithm in axes of mobile accelerometer, transition from activity of daily living (ADL) to forward fall event is recognized. In collected templates, Dynamic Time Warping (DTW) was applied to compute difference among them with new unlabeled samples. Results implemented on mobile phone easily show the feasibility of the method hence contribute significantly to fall detection in healthcare.

WeMos IoT Controller-Based Low-Cost Fall Detection System for Elderly Users

2021 ◽  
Vol 50 ◽  
pp. 59-72
Author(s):  
Mohammed Faeik Ruzaij Al-Okby ◽  
Kerstin Thurow
Keyword(s):  
False Positive ◽  
Detection System ◽  
Low Cost ◽  
False Negative ◽  
Lithium Ion ◽  
Fall Detection ◽  
The Elderly ◽  
The Body ◽  
Detection Systems ◽  
Alarm Message

Fall detection systems for the elderly are very important to protect this type of users. The early detection of the fall of the elderly has a major impact on saving their lives and avoiding the deterioration of the negative medical effects resulting from the effect of the patient falling on a hard surface. One of the constraints in fall detection systems are false-negative errors (no fall detection) or false-positive errors (sending a false warning without real fall accident). These errors have to be reduced significantly. In this paper, an innovative method to reduce fall detection system errors is proposed. The system consists of two orientation detection sensors to track the body orientation instead of using a single sensor in the previous systems which enhances the system accuracy and reduces the false-negative and false-positive errors. The system uses a small size IoT-based controller to process the sensor's information and make the alarm decision based on specific thresholds. The output alarm of the system includes an email sent to the caregivers via the embedded Wi-Fi ESP8266 module as well as an SMS message to the caregivers’ phones via GSM modules to ensure that the alarm message arrives in the absence of internet coverage for the patient or the caregiver. The system is powered by a small lithium-Ion battery. All sensors and modules of the system are combined in a small rubber box that can be fixed in a waist belt or the chest rejoin of the user body. Several tests have been made in different procedures. The tests revealed that the new approach improves the accuracy of the system and reduces the possibility of triggering wrong alarms.

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