Senior citizens who are a little weaker or frail are often prone to falling. The FRADE concept of the Fraunhofer Center AICOS in Porto, Portugal offers effective help with prevention. Sensor-based analysis of movements serves as a basis for a tailored training program. If the person actually falls, the system alerts the caregiver via text message. International Hospital reports.
Many older and frail people live with the risk of falling in their home and then possibly waiting hours for assistance, which is often a persistent fear for their families. This is also a problem for caregiversw ho visit their patients daily, but know that they will be unsupervised for several hours.
The Fraunhofer Center for Assistive Information and Communication Solutions (AICOS) in Porto, Portugal, developed the FRADE project specifically for this problem. FRADE stands for “pervasive platform for fall risk assessment, fall detection and fall prevention”. The central component is a sensor that is attached to the clothing. If the person wearing the sensor falls down, an alert is sent to the caregiver via text message. But this is just one part of the multistep concept.
“We want to prevent people from falling in the first place,” explains Project Manager Joana Silva.
Analysis of movements, assessment of the risk of falling
The first step in the FRADE concept is to assess the elderly or frail person’s risk of falling with a series of tests that analyse the person’s typical movements. Under the supervision of a therapist, the person performs various movements, which can include getting up from a chair, walking a few meters, and standing still, with each exercise repeated several times. An acceleration sensor attached to the ankle or the waist registers movements and sends the data via Bluetooth Low Energy (BLE) to a desktop computer.
A pressure-sensitive mat that measures the distribution of bodyweight on the soles of the feet is also used for certain exercises. A large display shows plantar pressure distribution as a graph in real time. The system is able to detect if pressure is applied to the feet unevenly – for example, when the person bends their knees – which may be an indication of balancing issues. The mat sends this measurement data to the computer via USB, where it is analysed by software equipped with specific algorithms.
“All of the data is compiled to create an individual movement profile, which we can use to determine the person’s risk of falling. That is one of the FRADE innovations,” explains Silva. All of the information finds its way to the back-end server, which also serves as a central data storage platform for caregivers.
The tailored training program for home
In the second step, the person is provided with a kit consisting of a sensor and Android tablet as well as a training program for home that is tailored to their individual movement profile and risk of falling. The training app shows in graphic form how to perform the movements. Once again, the wearable inertial sensor analyses the movements. A microprocessor integrated into the sensor processes all of the data and sends it to the tablet via BLE. Those who train on a regular basis – i.e. around two to three times a week – can isgnificantly reduce their risk of falling after a period of at least eight weeks.