Data acquisition system using six degree-of-freedom inertia sensor and ZigBee wireless link for fall detection and prevention

A Simplistic and Cost-Effective Design for Real-World Development of an Ambient Assisted Living System for Fall Detection and Indoor Localization: Proof-of-Concept

Falls, highly common in the constantly increasing global aging population, can have a variety of negative effects on their health, well-being, and quality of life, including restricting their capabilities to conduct activities of daily living (ADLs), which are crucial for one’s sustenance. Timely assistance during falls is highly necessary, which involves tracking the indoor location of the elderly during their diverse navigational patterns associated with different activities to detect the precise location of a fall. With the decreasing caregiver population on a global scale, it is important that the future of intelligent living environments can detect falls during ADLs while being able to track the indoor location of the elderly in the real world. Prior works in these fields have several limitations, such as the lack of functionalities to detect falls and indoor locations in a simultaneous manner, high cost of implementation, complicated design, the requirement of multiple hardware components for deployment, and the necessity to develop new hardware for implementation, which make the wide-scale deployment of such technologies challenging. To address these challenges, this work proposes a cost-effective and simplistic design paradigm for an ambient assisted living system that can capture multimodal components of user behaviors during ADLs that are necessary for performing fall detection and indoor localization in a simultaneous manner in the real-world. Proof-of-concept results from real-world experiments are presented to uphold the effective working of the system. The findings from two comparative studies with prior works in this field are also presented to uphold the novelty of this work. The first comparative study shows how the proposed system outperforms prior works in the areas of indoor localization and fall detection in terms of the effectiveness of its software design and hardware design. The second comparative study shows that the cost of the development of this system is the lowest as compared to prior works in these fields, which involved real-world development of the underlining systems, thereby upholding its cost-effective nature.

Fall detection devices and their use with older adults: a systematic review

BACKGROUND

Falls represent a significant threat to the health and independence of adults aged 65 years and older. As a wide variety and large number of passive monitoring systems are currently and increasingly available to detect when individuals have fallen, there is a need to analyze and synthesize the evidence regarding their ability to accurately detect falls to determine which systems are most effective.

OBJECTIVES

The purpose of this literature review is to systematically assess the current state of design and implementation of fall-detection devices. This review also examines to what extent these devices have been tested in the real world as well as the acceptability of these devices to older adults.

DATA SOURCES

A systematic literature review was conducted in PubMed, CINAHL, EMBASE, and PsycINFO from their respective inception dates to June 25, 2013.

STUDY ELIGIBILITY CRITERIA AND INTERVENTIONS

Articles were included if they discussed a project or multiple projects involving a system with the purpose of detecting a fall in adults. It was not a requirement for inclusion in this review that the system targets persons older than 65 years. Articles were excluded if they were not written in English or if they looked at fall risk, fall detection in children, fall prevention, or a personal emergency response device.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies were initially divided into those using sensitivity, specificity, or accuracy in their evaluation methods and those using other methods to evaluate their devices. Studies were further classified into wearable devices and nonwearable devices. Studies were appraised for inclusion of older adults in sample and if evaluation included real-world settings.

RESULTS

This review identified 57 projects that used wearable systems and 35 projects using nonwearable systems, regardless of evaluation technique. Nonwearable systems included cameras, motion sensors, microphones, and floor sensors. Of the projects examining wearable systems, only 7.1% reported monitoring older adults in a real-world setting. There were no studies of nonwearable devices that used older adults as subjects in either a laboratory or a real-world setting. In general, older adults appear to be interested in using such devices although they express concerns over privacy and understanding exactly what the device is doing at specific times.

LIMITATIONS

This systematic review was limited to articles written in English and did not include gray literature. Manual paper screening and review processes may have been subject to interpretive bias.

CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

There exists a large body of work describing various fall-detection devices. The challenge in this area is to create highly accurate unobtrusive devices. From this review it appears that the technology is becoming more able to accomplish such a task. There is a need now for more real-world tests as well as standardization of the evaluation of these devices.

Fall detection with body-worn sensors : a systematic review

BACKGROUND AND AIMS

Falls among older people remain a major public health challenge. Body-worn sensors are needed to improve the understanding of the underlying mechanisms and kinematics of falls. The aim of this systematic review is to assemble, extract and critically discuss the information available in published studies, as well as the characteristics of these investigations (fall documentation and technical characteristics).

METHODS

The searching of publically accessible electronic literature databases for articles on fall detection with body-worn sensors identified a collection of 96 records (33 journal articles, 60 conference proceedings and 3 project reports) published between 1998 and 2012. These publications were analysed by two independent expert reviewers. Information was extracted into a custom-built data form and processed using SPSS (SPSS Inc., Chicago, IL, USA).

RESULTS

The main findings were the lack of agreement between the methodology and documentation protocols (study, fall reporting and technical characteristics) used in the studies, as well as a substantial lack of real-world fall recordings. A methodological pitfall identified in most articles was the lack of an established fall definition. The types of sensors and their technical specifications varied considerably between studies.

CONCLUSION

Limited methodological agreement between sensor-based fall detection studies using body-worn sensors was identified. Published evidence-based support for commercially available fall detection devices is still lacking. A worldwide research group consensus is needed to address fundamental issues such as incident verification, the establishment of guidelines for fall reporting and the development of a common fall definition.

Review of wireless sensors networks in health applications

Wireless Sensor Networks (WSN) are becoming increasingly important for telemedicine applications, monitoring patients both in the clinical setting and at home. They reduce user discomfort, enhance mobility and reduce costs. WSN are also fundamental in Ambient Assisted Living (AAL) since these smart systems, which are tailored to users needs, collect information about users and their ambient in order to provide personalized feedback. Despite the growing use of wireless communications in the health domain and in AAL systems there is a lack of research literature reviewing trials of these technologies. This paper provides a systematic review of the use of WSN in the health domain, presenting current WSN implementations. It covers 126 papers, of which 26 are studies, classified according to inclusion criteria. There is presented a discussion about the recent research conducted in the field.

An environmental-adaptive fall detection system on mobile device

When facing damages caused by falls, a well designed smart sensor system to detect falls can be both medically and economically helpful. This research introduces a portable terrain adaptable fall detection system, by placing accelerometers and gyroscopes in parts of the body and transmit data through wireless transmitter modules to mobile devices to get the related information and combining it with the center of gravity clustering algorithm introduced in this research which computes the human body behavior patterns according the relationship between the center of gravity in the body and the feet portion of the body. Compared with the research in the past, this system is not only highly accurate and robust, but also able to adapt to different types of terrains, which solves the problems that other researches have for detection errors when the client is climbing the stairs or walking on a slant.