"Experts insist that measuring the state of health of the elderly population needs to be done in terms of function and not disease. So it is crucial to know their functional capacity prior to the development of disability or dependence to be able to mitigate its effects," pointed out Nora Millor.
Millor chose the frailty syndrome for her work because "those who suffer from it, in particular the elderly, face a greater risk of deterioration in their health and functional state. It is defined as a syndrome because it includes a set of symptoms that in this case render the person with them more vulnerable in the face of any factor," she explained. "Until now one of the most used methods to diagnose it has been the Fried criterion, which is based on the presence of three or more of these components: slowness in walking, weakness, weight loss, fatigue and low physical activity. So the subjects are classified as frail if they meet three or more criteria; pre-frail if they meet one or two; and healthy if they don't meet any of them".
However, in the view of the new PhD holder, the problem of assessments of this type is that "it is not easy to determine these components and, what is more, the experience of the person who makes the diagnosis plays a significant role, so the result tends to be more qualitative than quantitative".
In order to come up with some objective measurements, Nora Millor studied the frailty syndrome taking as the basis one of the tests used in geriatrics to measure the state of the patients: the 30-second chair test. "Getting up from a chair is one of the activities in daily life that poses the greatest level of mechanical and muscular demand. A proportion of the elderly population has serious difficulties in being able to do this, so they spend more time sitting and their capacity to live independently is reduced," she said. The test is based on the number of times a person is capable of getting up from a chair and sitting down during the thirty seconds the test lasts.
Measuring by means of sensors
Nora Millor used inertial sensors capable of providing information about how a specific moment has been carried out in a way that is "non-invasive, portable and economic". Specifically, they provide data on acceleration (the speed at which the movement varies) and angular speed (how fast a turn is made). "This not only provides data on the amount of movement, but also on how it has been made," said Nora Millor, who received the grade of distinction "cum laude".
Nora Millor has specified new parameters from the analysis of the signals provided by the inertial sensors; this means that clinical staff can now avail themselves of "a series of objective, quantifiable measurements to make their diagnoses. In the future, the results could be built into a user-friendly tool such as a mobile app," predicted Millor.