Human Gait Monitoring: Methods And Systems Using Wearable Technologies

Nome: Laura Susana Vargas Valencia
Tipo: Tese de doutorado
Data de publicação: 24/09/2019

Nomeordem decrescente Papel
Anselmo Frizera Neto Orientador
Teodiano Freire Bastos Filho Co-orientador


Nomeordem decrescente Papel
Adriano Almeida Gonçalves Siqueira Examinador Externo
Anselmo Frizera Neto Orientador
Eduardo Rocon de Lima Examinador Externo
Luiz Eduardo Rodríguez Cheu Examinador Externo
Patrick Marques Ciarelli Examinador Externo
Teodiano Freire Bastos Filho Coorientador

Resumo: Several diseases and accidents can lead to motor impairments, preventing humans from normal daily life activities. In order to diagnose and treat the population suffering from walking disabilities, clinicians and physical therapists need tools that help to asses and analyze patients’ gait pattern. Moreover, sports science is another field that can benefit from joint motion analysis. Researchers, coaches and athletes may need a suitable tool to monitor movements seeking to enhance their performance. Nowadays, the gold standard in motion assessment are systems comprised by infrared high speed cameras and reflective markers, the last placed commonly on subjects’ anatomical landmarks. Such systems are highly expensive and require a dedicated environment, limiting their use to indoors ambients and constrained spaces. Also, these limitations factors impede their use in most hospitals and physical therapy clinics. Furthermore, in sport related activities, limitations imposed by camera-based motion analysis laboratories are even more critical, since the space constrains may restrict sport real activities. New sensor approaches are now shifting the paradigm from the bulk and expensive systems to wearable and more affordable technologies. Among others, inertial measurement units (IMU) are being widely used to assess human movements with little interference to user activities. IMU sensors often consist of accelerometers, gyroscopes and magnetometers incorporated in the same unit. Moreover, recent studies have demonstrated the feasibility of using optical fiber based curvature sensors to measure joint angles. Their adaptability, low-cost, light-weight and electromagnetic immunity are features that make them an interesting alternative technology. As a first contribution of this Ph.D thesis, we present a novel calibration procedure as a method to align IMU sensors to body segments, which compared to other methods in the literature, is based on fast and simple sensor placement, with no need predefined nor any additional tools. The promising results demonstrate the potential of this IMU-to-body alignment method to become an alternative to high-cost camera-based systems allowing the possibility of performing the analysis of human gait in external environments with clinical application in the near future. As a second contribution of this Ph.D thesis, we have developed a novel IMU-POF sensor fusion system for knee angle monitoring, which consist of merging data from two inertial sensors and a polymeric optical fiber (POF) curvature sensor. The algorithm implementation relies more on IMU sensors or POF curvature sensor data depending on the gait cycle phase, generating a filtered output that is more accurate than any of the independent sensors. Our proposed methods and system presented better performance (mean RMSE < 3.3°, LFM coefficients, a1 = 0.99±0.04, a0 = 0.70 ± 2.29, R2 = 0.98 ± 0.01 and pc>0.99) when compared with other methods in the literature. In summary, this Ph.D. thesis contribute to the state-of-the-art in the use of wearable technologies for motion analysis by improving the accuracy and usability of new systems towards in-home motion monitoring and clinical scenarios.

Keywords: Inertial sensor, polymeric optical fiber, IMU alignment, multiplicative extended Kalman filter, gait analysis.

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