More than a third of all over 65-year-old people in Germany are in acute danger of falling. The consequences concern themselves, their personal environment, but also the health system. Electrical engineers from the Karlsruhe Institute of Technology (KIT) want to remedy this situation with new sensor technology that focuses on movements and the environment, making it possible to assess the risk of falls and recommend suitable measures to prevent falls. Currently, the researchers continue to develop the prototype together with an industry partner.
“We want to make the assessment of the risk of falling just when it is needed, so in the home environment of the vulnerable person,” says Tomislav Pozaic, who has written his thesis on the subject at the Institute for Information Technology (ITIV) of the KIT. So far, such a review was done only in geriatric hospitals in connection with rehabilitation measures or as a fall diary of patients. “Often, one or more crashes have happened before. That’s why we want to continuously raise the risk of falling, in order to prevent the first crash, “says the electrical engineer.
“Depressive moods or mild colds can already increase the risk of falling. Therefore, it is important to recognize this early and to counteract with activation measures such as coordination training, “explains Professor Wilhelm Stork, Pozaic’s supervisor and head of the microsystem technology department at the ITIV. The costs for the health care system must also be considered: “More than two billion euros will be required for follow-up treatment of falls per year,” says Tomislav Pozaic.
In a large clinical study in collaboration with the geriatric department of the Robert Bosch Hospital in Stuttgart under the direction of Professor Clemens Becker, the working group has investigated how wrist joint sensors, which capture both movement and the environment, can be used to prevent falls. The sensors that they develop evaluate the number and type of steps as well as the speed and movement. In addition, they are able to put them in the environment context. “Different environments, such as the street compared to your own home, lead to different risks,” says Pozaic.
An algorithm converts the measured values from the sensor into a figure that stands for the risk of falling – ie “endangered” or “not endangered”. In the case of vulnerable persons, the system continues to differentiate between persons who have fallen one time or one or more recurrent fallers.
“The advantage of the technology is that it can be used in everyday life at home and thus, if necessary, it can also convey directly to the doctor the information concerning the specific environment of the patient. This saves on one hand, and on the other hand preventive measures can be more easily adapted to the home environment of the patient, “Stork concludes.
Information from three areas of movement – gait, person standing up and arm-leg coordination – are evaluated to choose the correct strategy against falls. These strategies include balance training, drug adjustments, and minimizing household dangers.
In addition to the pure fall risk analysis, Pozaic pursued another goal, which is strongly related to the consequences of falls for the mental health of those affected: “Our focus was on an unobtrusive design that does not stigmatize. People who have fallen several times feel that they have to be labeled as needy due to obvious preventive measures. This allows the sensor to be worn inconspicuously like a watch on the wrist but transmits vital information. ”
The sensors are currently undergoing further development together with Bosch Healthcare Solutions and could be launched in the next few years.
Source : Karlsruhe Institute of Technology (KIT)