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Ponciano, V., Pires, I. M., Ribeiro, F. R., Garcia, N. M. (2020).
Data acquisition of timed-up and go test with older adults: accelerometer, magnetometer, electrocardiography and electroencephalography sensors’ data.
Data in Brief, 32, 106306.
https://doi.org/10.1016/j.dib.2020.106306

Ponciano, V., Pires, I.M., Ribeiro, F.R. et al. (2020).
Sensors are Capable to Help in the Measurement of the Results of the Timed-Up and Go Test? A Systematic Review.
Journal of Medical Systems, 44, 199.
https://doi.org/10.1007/s10916-020-01666-8

Ponciano, V., Pires, I. M., Ribeiro, F. R., Marques, G., Garcia, N. M., Pombo, N., Spinsante, S., Zdravevski, E. (2020).
Is The Timed-Up and Go Test Feasible in Mobile Devices? A Systematic Review.
Electronics, 9(3), 528.
https://doi.org/10.3390/electronics9030528

Ponciano, V., Pires, I., Ribeiro, F., Marques, G., Garcia, N. M., Zdravevski, E., Spinsante, S (2020).
Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review.
Electronics, 9(5), 778.
https://doi.org/10.3390/electronics9050778

Ponciano, V., Pires, I. M., Ribeiro, F. R., Villasana, M. V., Crisóstomo, R., Teixeira, M. C., Zdravevski, E. (2020).
Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults.
Sensors, 20(12), 3481.
https://doi.org/10.3390/s20123481

Ponciano, V., Pires, I. M., Ribeiro, F. R., Garcia, N, M., Villasana, M. V., Zdravevski, E., Lameski, P. (2020).
Machine Learning Techniques with ECG and EEG Data: An Exploratory Study.
Computers, 9(3), 55.
https://doi.org/10.3390/computers9030055

Ponciano, V., Pires, I. M., Ribeiro, F. R., Villasana, M. V., Teixeira, M. C., Zdravevski, E. (2020).
Experimental Study for Determining the Parameters Required for Detecting ECG and EEG Related Diseases during the Timed-Up and Go Test.
Computers, 9(3), 67.
https://doi.org/10.3390/computers9030067