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Publications

Publications by C-BER

2018

Innovative analysis of 3D pelvis coordination on modified gait mode

Authors
Rodrigues, C; Correia, MV; Abrantes, JMCS; Nadal, J; Rodrigues, MAB;

Publication
Lecture Notes in Computational Vision and Biomechanics

Abstract
This study presents innovative analysis at the time, frequency and phase domain of the pelvis angular oscillation at transverse (T), sagittal (S) and coronal (C) planes, assessing its coordination during stiff knee gait (SKG) and slow running (SR) comparing it to normal gait (NG). Case study is considered of an adult male 70 kg mass and 1.86 m height. Computer vision is used with 8 Qualysis 100 Hz cameras tracking position of right and left anterior and posterior superior iliac spine (RAsis, LAsis, RPsis, LPsis) including one complete stride during NG, SKG and SR. 3D position coordinates are obtained from 2D image coordinate of multiple camera image using direct linear transformation (DLT). Inverse kinematics is performed using cartesian position data of RAsis, LAsis, RPsis, LPsis and scaled model to subject dimension. The angles, angular velocities and angular accelerations coordination of the pelvis oscillation at T, S, C planes were assessed using linear and cross correlation analysis (LCA, CCA), fast Fourier transform (FFT) and phase space analysis (PSA). Results point for important complementary analysis on entire series of time, frequency and phase analysis of human movement such as the pelvis coordination assessment on different gait modes. © 2018, Springer International Publishing AG.

2018

Sclinico: Usability study

Authors
Pavão, J; Bastardo, R; Covêlo, M; Pereira, LT; Oliveira, P; Pedrosa, C; Silva, A; Costa, V; Martins, AI; Queirós, A; Rocha, NP;

Publication
HEALTHINF 2018 - 11th International Conference on Health Informatics, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018

Abstract
The use of electronic health records (EHR) to support clinical practices is widespread worldwide, due to the need to optimize health care delivery. Therefore, the usability assessment of EHR systems is crucial. The objective of this study was to perform a qualitative and quantitative assessment of the usability of SClinico, the most used EHR system within the Portuguese National Health Service. This observational study to assess SClinico usability took place in several clinical services of the Centro Hospitalar de Trás-os-Montes e Alto Douro. The results show that SClinico has some usability issues that influence the clinical practice and, therefore, need to be improved. Copyright

2018

Optical Fiber Tips for Biological Applications: from Light Confinement, Biosensing to Bioparticles Manipulation

Authors
Paiva, JS; Jorge, PAS; Rosa, CC; Cunha, JPS;

Publication
Biochimica et Biophysica Acta (BBA) - General Subjects

Abstract

2018

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

Authors
Paiva, JS; Ribeiro, RSR; Cunha, JPS; Rosa, CC; Jorge, PAS;

Publication
Sensors

Abstract

2018

Skin temperature of the foot: A comparative study between familial amyloid polyneuropathy and diabetic foot patients

Authors
Seixas, A; Vilas Boas, MD; Carvalho, R; Coelho, T; Ammer, K; Vilas Boas, JP; Vardasca, R; Silva Cunha, JPS; Mendes, J;

Publication
Lecture Notes in Computational Vision and Biomechanics

Abstract
Skin temperature regulation is dependant of the autonomic nervous system function, which may be impaired in patients with neuropathy. Studies reporting thermographic assessment of patients with established diagnosis of Diabetic Foot (DF) are scarce but this information is completely absent in patients suffering from Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP). The aim of this study is to compare skin temperature distribution in patients with DF and TTR-FAP. Thermograms of the dorsal and plantar surfaces were compared. Skin temperature was higher in the diabetic foot group and differences were statistically significant (p < 0.05) in both regions of interest. © 2018, Springer International Publishing AG.

2018

Quantification of gait parameters with inertial sensors and inverse kinematics

Authors
Boetzel, K; Olivares, A; Cunha, JP; Gorriz Saez, JMG; Weiss, R; Plate, A;

Publication
Journal of Biomechanics

Abstract
Measuring human gait is important in medicine to obtain outcome parameter for therapy, for instance in Parkinson's disease. Recently, small inertial sensors became available which allow for the registration of limb-position outside of the limited space of gait laboratories. The computation of gait parameters based on such recordings has been the subject of many scientific papers. We want to add to this knowledge by presenting a 4-segment leg model which is based on inverse kinematic and Kalman filtering of data from inertial sensors. To evaluate the model, data from four leg segments (shanks and thighs) were recorded synchronously with accelerometers and gyroscopes and a 3D motion capture system while subjects (n = 12) walked at three different velocities on a treadmill. Angular position of leg segments was computed from accelerometers and gyroscopes by Kalman filtering and compared to data from the motion capture system. The four-segment leg model takes the stance foot as a pivotal point and computes the position of the remaining segments as a kinematic chain (inverse kinematics). Second, we evaluated the contribution of pelvic movements to the model and evaluated a five segment model (shanks, thighs and pelvis) against ground-truth data from the motion capture system and the path of the treadmill. Results: We found the precision of the Kalman filtered angular position is in the range of 2–6° (RMS error). The 4-segment leg model computed stride length and length of gait path with a constant undershoot of 3% for slow and 7% for fast gait. The integration of a 5th segment (pelvis) into the model increased its precision. The advantages of this model and ideas for further improvements are discussed. © 2018 Elsevier Ltd

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