INBED: A Highly Specialized System for Bed-Exit-Detection and Fall Prevention on a Geriatric Ward

Abstract

Objective: In geriatric institutions, the risk of falling of patients is very high and frequently leads to fractures of the femoral neck, which can result in serious consequences and medical costs. With regard to the current numbers of elderly people, the need for smart solutions for the prevention of falls in clinical environments as well as in everyday life has been evolving. Methods: Hence, in this paper, we present the Inexpensive Node for bed-exit Detection (INBED), a comprehensive, favourable signaling system for bed-exit detection and fall prevention, to support the clinical efforts in terms of fall reduction. The tough requirements for such a system in clinical environments were gathered in close cooperation with geriatricians. Results: The conceptional efforts led to a multi-component system with a core wearable device, attached to the patients, to detect several types of movements such as rising, restlessness and—in the worst case—falling. Occurring events are forwarded to the nursing staff immediately by using a modular, self-organizing and dependable wireless infrastructure. Both, the hardware and software of the entire INBED system as well as the particular design process are discussed in detail. Moreover, a trail test of the system is presented. Conclusions: The INBED system can help to relieve the nursing staff significantly while the personal freedom of movement and the privacy of patients is increased compared to similar systems.

Implementation and experience of an innovative smart patient care system: a cross-sectional study

“…Hospital falls commonly occur between 5 pm and 7 am in a patient’s room when staffing levels are lower, and a large number of falls are related to getting in and out of bed [ 13 ]. In clinical practice, it is common to use bed-exit detection systems, such as mattresses/pads, cameras, and wearable devices, to help notify nurses about bed-exit situations for patients who are at high risk of falling [ 44 , 45 ]. The effect of these systems on fall prevention, however, is inconclusive [ 46 , 47 ].…”

Design and Implementation of a Wearable Accelerometer-Based Motion/Tilt Sensing Internet of Things Module and Its Application to Bed Fall Prevention

“…This algorithm enables performing the data conversion process within the BLE SoC along with the original firmware, which handles all BLE communication protocols. Unlike the wearable sensor described in [ 29 ], which required a separate processor, IMU, and wireless communication module (Zigbee, 802.15.4), the BASIC module obviates the need for an extra microcontroller for data collection and conversion into tilt angle information, thus, its cost and power consumption can be further reduced. The BLE unit used in the BASIC module is nRF52832 (NORDIC Semiconductor, Oslo, Norway), a Class 2, BT5.0 BLE module with a built-in antenna.…”

“…Fall prediction systems could depend on various indicators. Jähne-Raden et al [ 29 ] developed a system, INBED, for bed exit detection and fall prevention in a geriatric ward by detecting the wakefulness of patients in sleep before their intentions to get out of beds. The system involves a wearable sensor with an inertial measurement unit (IMU), including an accelerometer and a gyroscope, that is attached to a patient’s thigh.…”

Effectiveness of an integrated three‐mode bed exit alarm system in reducing inpatient falls within an acute care setting

“…These devices are designed to act as an early warning system which detects and alerts nurses to patients who are trying to egress from their beds unassisted; presumably, it would allow sufficient time for nurses to attend to the patient before a fall occurs (LeLaurin & Shorr, 2019). There are various types of bed exit alarm sensors available, and they are differentiated by two main classes: ambient and body‐worn variants (Jähne‐Raden et al ., 2019). These alarm systems may be presented in various forms such as: mattress pad systems, floor pressure mats, infra‐red lasers, cameras, and devices clipped onto patients' garments; with each device bearing certain pros and cons (Jähne‐Raden et al ., 2019).…”

“…There are various types of bed exit alarm sensors available, and they are differentiated by two main classes: ambient and body‐worn variants (Jähne‐Raden et al ., 2019). These alarm systems may be presented in various forms such as: mattress pad systems, floor pressure mats, infra‐red lasers, cameras, and devices clipped onto patients' garments; with each device bearing certain pros and cons (Jähne‐Raden et al ., 2019).…”