Smart-cane is an open hardware and open software project created to promoting an active ageing. This project was created on Integrated Systems Engineering group, on Department of Electronic Technology (Málaga University). Nowadays, it is carried out at MDH University at the Biomedical Engineering group in collaboration with Integrated Systems Engineering group.
The project is led by Dr. Ballesteros and it counts with the help of M.Sc. Alberto Tudela, B.Sc. Juan Caro and the support of Prof. Dr. Maria Lindén and Prof. Dr. Cristina Urdiales.
This project is focused on adding on-board sensors to the cane to monitor users. These sensors should be affordable in order to reduce the cost and to increase the number of end users. Force sensors and hall effect sensors are being testing to measure the weight-bearing and other significant parameters related with an active ageing. The results are been validated in collaboration with the following Senior centres (Centros de participación activa) in Córdoba (Spain): CÓRDOBA II, FUENSANTA – CAÑERO, PONIENTE, LOS NARANJOS.
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Fusion 360 - The program used to to design the plastic pieces. All these documents have been exported to STEP file extension too. It is an ISO standard exchange format that can be openned by other programs, such as FreeCAD.
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MBED online compiler - The online program used to to programming the BLE Nano v1 microcontroller.
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Android Studio - The program to create the mobile software.
- Joaquín Ballesteros - Team leader, design and programming - joaquinballesteros
- Alberto Tudela - Electronic and 3D models - ajtudela
- Juan Caro - Electronic and software - jrcaro
Contact: jballesteros@uma.es
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Swedish Knowledge Foundation (KKS) through the research profile Embedded Sensor Systems for Health at Mälardalen University, Sweden - Prof. Dr. Maria Lindén.
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Plan Propio de la Universidad de Málaga (Proyectos Puente) at Málaga University, Spain - Prof. Dr. Cristina Urdiales.
This project is licensed under the Creative Commons Attribution 4.0 - see the LICENSE.md file for details.
The authors would like to thank to Ms. Luna Ruiz who greatly assisted every single test.
Ballesteros, J., Tudela, A., Caro-Romero, J. R., & Urdiales, C. (2019). Weight-bearing estimation for cane users by using onboard sensors. Sensors, 19(3), 509. link
Ballesteros, J., Tudela, A., Caro-Romero, J. R., & Urdiales, C. (2019, May). A cane-based low cost sensor to implement attention mechanisms in telecare robots. In 2019 International Conference on Robotics and Automation (ICRA) (pp. 1473-1478). IEEE.link
Caro-Romero, J. R., Ballesteros, J., Garcia-Lagos, F., Urdiales, C., & Sandoval, F. (2019, June). A Neural Network for Stance Phase detection in smart cane users. In International Work-Conference on Artificial Neural Networks (pp. 310-321). Springer, Cham.link
Ayala, I., Ballesteros, J., Caro-Romero, J. R., Amor, M., & Fuentes, L. (2019). Self-Adaptation of mHealth Devices: The Case of the Smart Cane Platform. In Multidisciplinary Digital Publishing Institute Proceedings (Vol. 31, No. 1, p. 23).link