**4. Conclusions**

In the project fast care, a real-time capable sensor data analysis-framework in the fields of ambient assisted living was developed. The project realized a medical valid integrated real-time picture of the patient's situation by using several interconnected sensor-actor infrastructures with a latency period of less than 10 ms.

#### *Real-Time Capable Sensor Data Analysis-Framework for Intelligent Assistance Systems DOI: http://dx.doi.org/10.5772/intechopen.93735*

The implemented sensor structure records the heart rate, the breathing rate, the VOC content of the room air, analyzes the gait for rehabilitation and measures the temperature and humidity in the room. An emergency button has also been integrated.

An active prosthetic foot was used as a special application of the sensor-actor System. Its running parameters can be measured online, and the prosthesis can automatically adapt to the floor covering and the running demands via the network. This means that users have an intelligent active prosthesis at their disposal to help them cope with everyday life more easily.

It was shown that even with a heterogeneous network consisting of the components WiFi, Bluetooth LE, Gigabit LAN and 4G+, real-time operation was possible for the use of the AAL components. Even the display of the measured data, which was transferred to a website via the cloud, only showed latencies of an additional few milliseconds. This made it possible to create a real-time image in the form of an Avatar for all vital parameters and the automatic setting of the active prosthetic foot, which enables the client to notice his physical condition in situ.

In addition to the technical development activities, an analysis of acceptance was executed at the demonstrator in the AAL-laboratory. The survey results of the entire system were very positive. 60% of the respondents stated, that they would like to use the technology privately, 70% of the respondents would like to have access to the technology, 35% would be willing to buy the presented technology and 95% see a great benefit for themselves and for others in the tested technology.

Unfortunately, some slow network technologies such as Bluetooth LE had to be used to carry out the project. It is to be expected, that with the full expansion of the networks to the fifth generation (5G), there will still be a significant leap in transmission speed and transmission quality. It is therefore to be expected that eHealth applications in the home area can be implemented in real time in the near future. After the data fusion, further processing with the help of the artificial intelligence will bring further benefits to the client for the prevention of his physical and mental health.

#### **Acknowledgements**

The fast care project was supported by the German Federal Ministry of Education and Research in the program "Zwanzig20 – Partnerschaft für Innovation", contract no. 03ZZ0519I. It was carried out in the form of a joint project with eight partners and a project coordinator. We thank all fast care project partners for their contributions to this work personally listed in the following: Thomas Kirste, Christian Haubelt, Albert Hein, Florian Grützmacher from University Rostock, Ernst Albrecht-Laatsch, Bernhard Graimann, Martin Schmidt and Katharina Olze from Ottobock, Alexander Trumpp, Daniel Wedekind, Martin Schmidt, Sebastian Zaunseder, Hagen Malberg from Technische Universität Dresden, Christian Reinboth and Jens-Uwe Just from HarzOptics, Matthias Stege, Frank Schäfer, Tristan Heinig and Sascha Huth from Exelonix, Rainer Dorsch from Bosch Sensortec, Lutz Schega, Sebastian Stoutz and Kim-Charline Broscheid from Otto-von-Guericke-Universität Magdeburg.

Analyzing the system of the TU Dresden, the success of the measurement was rated 4.05 out of 5 points and the comprehensibility of the instructions with 4.05 out of 5 points. The comprehensibility of the instructions was more incomprehensible for the test subjects when they were overwhelmed by the technology. The intelligibility of the display and the results was rated with 3.58 out of 5 points

*Evaluation of the applications of the demonstrators of OvGU and TU Dresden.*

In the project fast care, a real-time capable sensor data analysis-framework in the fields of ambient assisted living was developed. The project realized a medical valid integrated real-time picture of the patient's situation by using several

interconnected sensor-actor infrastructures with a latency period of less than 10 ms.

(see **Figure 20**).

**Figure 20.**

**Figure 19.**

*Evaluation of the application of the active prothetic foot.*

*Data Acquisition - Recent Advances and Applications in Biomedical Engineering*

**4. Conclusions**

**24**

*Data Acquisition - Recent Advances and Applications in Biomedical Engineering*

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*DOI: http://dx.doi.org/10.5772/intechopen.93735*

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