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SmartReminders – Tests with sensors

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COLABORAR provided users to test the sensors used to detect the movements of the arm. This sensors are being used in the scope of the thesis SmartReminders, under development at Fraunhofer AICOS, with the purpose of monitoring daily activities such as eating or drinking.

The first tests were conducted with a sample of 20 seniors at a day-care centre. Participants had the sensors in their wrists while taking their meals.

Thank you all participants! You always receive us warmly at the centre!

Tests for FallSensing

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Fraunhofer Portugal AICOS has been developing interactive games for fall prevention (project FallSensing) and we have just made the first tests with older adults at a Day Care Centre in Porto.

We took equipment to the centre and introduced the game. Then, we let participants try out the game and have fun! Researchers and the designer working on this project performed some observations and were happy to see how seniors organized to participate and how they interacted with each other, building teams and socialize around the new game.

We will be back soon to the centre to test new games!

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Active@Home: first tests with users at the Living Lab

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COLABORAR organized a session of tests for the project Active@Home.

Within this project, television games for physical exercise and fall prevention are being designed and developed. Users must use some sensors to detect physical movements, as well. In this first test session  with real end users, researchers tested the acceptance of the demo and collected some datasets using the sensors.

Participants seemed to enjoy and we are grateful for the precious help!

World Diabetes Day

November 14th is World Diabetes Day. The day was created by the International Diabetes Federation to help increase Diabetes awareness. Diabetes is a disease that affects people worldwide and its complications are blindness, heart attack, kidney failure and limb amputation. Blindness and amputation are consequences of Diabetic Rethinopathy and Diabetic Neuropathy, respectively. Researchers from  Fraunhofer Portugal AICOS are developing new solutions to improve the early detection of these Diabetes complications. COLABORAR wants to mark the date by highlighting those projects:

  • EyeFundusScope – “Mobile-based risk assessment of Diabetic Retinopathy by image processing” comprises an ophthalmoscopic adapter attached to a smartphone with an application that processes the images of the eye fundus captured by the optical adapter. The app allows the detection of micro-aneurysms, which are the first visible signs of Diabetic Rethinopathy, on an non-expert monitoring context, enabling an early pre-diagnosis;
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  • NeuropathyDetect – “Detection of Peripheral Neuropathy in Diabetes patients” consists of using plantar pressure sensors and smartphone built-in accelerometers to collect gait data that is then analyzed by a mobile application. It enables to identify early signs of Diabetic Peripheral Neuropathy in diabetic patients who therefore must adopt protective measures to prevent feet injuries and be followed-up by their medical doctor, in order to improve their treatment.
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You can see a news piece by SIC Notícias on these two Fraunhofer Portugal AICOS’s projects below (in Portuguese).

SmartRecovery: tests with patients

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The Master Thesis “Gait analysis in patients recovering from total joint replacement using body fixed sensors” (SmartRecovery) aims to study the gait of patients after a Total Knee Replacement (TKR), by measuring body movements, body mechanics and the activity of the muscles.

Several tests were conducted with the experimental group, comprised by patients recovering from TKR, and the control group, comprised by senior volunteers of COLABORAR. The tests took place respectively at the hospital and at Fraunhofer. The tests with volunteers will enable to differentiate the gait of patients who underwent a Total Knee Replacement and highlight the changes of gait between them and the people who did not undergo surgery for TKR.

NeuropathyDetect: tests for early detection of Neuropathy in people with Diabetes

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Some patients affected by Diabetes could develop Peripherical Neuropathy. At Fraunhofer Portugal, in the scope of the Master Thesis NeuropathyDetect, researchers are studying the gait of people with Diabetes. COLABORAR recruited volunteers for the tests, consisting in gait tests using sensors. Researchers could analyse the walking patterns of people with and without diabetes.

Thank you to all the participants, both at the centers and Fraunhofer’s facilities, for participating in the tests, allowing researchers to take an important step towards the identification of early signs of peripheral neuropathy in people with Diabetes.

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Kneegraphy: tests with volunteers

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In the scope of the Master Thesis “Classification of knee arthropathy with accelerometer-based vibroarthrography” (KneeGraphy), researchers are studying the knees of people with knee osteo-arthropathy, which is a condition that affects many seniors. In order to do so, researchers are developing an accelerometer-based system for knee data acquisition and data feature extraction for the differentiation between a pathological and a non-pathological knee. Several tests were conducted with seniors diagnosed with knee osteo-arthropathy and other volunteers for the control group.

Tests for the thesis mActivityClassify

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A prototype has been developed in the scope of the master thesis mActivityClassify. This is a solution that allows to classify activities of daily living. It consists of a real time classification algorithm using an Android smartphone in the pocket and an external smartwatch in the forearm. We asked participants to try out the system, by making some everyday gestures we use in activities of daily living.

The correct assessment of different activities can  be directly applied in the gamification of rehabilitation exercises for patients in the process of post-stroke rehabilitation.

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ExerGames and ExerBalance tested by volunteers

If we add a playful component through games to the conventional gymnastics exercises, the result is a platform of serious games. It is so called because they are games and because they have a serious purpose: fall prevention.

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Falls are an important problem among the elders. According to Sociedade Portuguesa de Ortopedia e Traumatologia, 30% of seniors have experienced a fall at least once. Our proximity to the seniors of the user network COLABORAR allows us know that 52% of the COLABORAR’s seniors have also experienced a fall, at least once. In addition to the high mortality and morbidity rates, the fear of falling is a serious concern among seniors and can even limit their activities.

The games of the ExerGames, developed in the scope of the Fall Competence Center (FCC) of Fraunhofer Portugal, were developed so that elders can perform exercises of muscle strengthening and balance training at home and have fun doing while doing it, reducing their fall risk.

In this testing phase, researchers want to know if all games are intuitive and, on the other hand, if the functioning is appropriate, bearing in mind that there are different patterns of use.

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A group of volunteers have already tested the ExerGames: both the user interfaces and the execution of the gym workouts. For these testing sessions, we had the new TV interfaces and a  platform that enables full-body tracking and body balance. The integration of this platform in the ExerGames was made in the scope of a master thesis entitled ExerBalance and received an excellent feedback from the participants as well. The ExerBalance might be used in the future, in the process of rehabilitation of persons with balance instability.

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Tests for EMGesture: using electromyography sensors in rehabilitation

May is that time of the year when the Master students are counting down the days to finish their theses. And after a period of hard work developing new Information and Communication solutions, this is also the moment to test their features. They know they can count on the volunteers of COLABORAR to help in that important phase.

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In the scope of the Master Thesis EMGesture, we asked participants to use sensors of surface electromyography and also inertial measurement sensors attached to the arm and perform some hand, wrist and forearm gestures. At the same time, students were verifying the correct functioning and accuracy of the system by analysing the detection of arm movements and the recognition of the hand gestures.

This technology is very promising, as it can be applied not only in the context of human-computer interaction, but also in the areas of functional rehabilitation and fall prevention.

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