On the use of sample entropy and quantized dynamical entropy of human gait signals as biomarkers of increased fall risk: experimental data analysis
| dc.contributor.author | Ahmadi, Samira | |
| dc.contributor.examiningcommittee | Luo, Yunhua (Mechanical Engineering) Wu, Christine (Mechanical Engineering) Annakkage, Udaya (Electrical and Computer Engineering) Fotouhi, Reza (Mechanical Engineering, University of Saskatchewan) | en_US |
| dc.contributor.supervisor | Sepehri, Nariman (Mechanical Engineering) Szturm, Tony (Physical Therapy) | en_US |
| dc.date.accessioned | 2019-07-26T19:33:01Z | |
| dc.date.available | 2019-07-26T19:33:01Z | |
| dc.date.issued | 2019 | en_US |
| dc.date.submitted | 2019-07-22T17:06:47Z | en |
| dc.degree.discipline | Mechanical Engineering | en_US |
| dc.degree.level | Doctor of Philosophy (Ph.D.) | en_US |
| dc.description.abstract | Identifying people who are at risk of fall during walking is crucial. The objective of this thesis is to comprehensively evaluate the application of two selected entropy measures, sample entropy (SampEn) and quantized dynamical entropy (QDE), as biomarkers of increased fall risk when applied to whole gait signals. SampEn is the most used entropy measure in human gait studies and QDE has the robustness of SampEn to noise but offers a superior computational performance. The first study further investigates the viability of SampEn and QDE along with choosing the signal which best discriminates between young healthy adults and elderly fallers as well as between walk only and dual-task walking condition. The results suggest that, amongst the five different signals representing trunk motion, leg motion, and the center of pressure of feet displacement, the center of pressure in the mediolateral direction (ML COP-D) is the best signal. The second study establishes the sensitivity of the SampEn and QDE of the ML COP-D signal to two preprocessing methods and to variant values of template size, tolerance size, and sampling rate. The results suggest that SampEn and QDE benefit from a relative consistency across variant parameter values, showing a significant increase from walk only to dual-task walking condition, especially when signals are low-pass filtered. Finally, the correlation of SampEn and QDE with two other families of gait measures (i.e., variability measures and the short-term largest Lyapunov exponent [LLE] measure), which have been used for gait stability assessment, is investigated. Two difficulty levels for the secondary visuomotor cognitive games are used. The results show that all gait measures increase due to dual-tasking, except for the short-term LLE which increases significantly only during the easy game. Additionally, these measures are not sensitive to the degree of difficulty of the secondary tasks. This is along with a poorer task performance when participants perform the secondary task while walking as compared to stationary standing. Only one variability measure, dispersion of foot placement in the mediolateral direction, is positively correlated with SampEn and QDE. Overall, the SampEn and QDE of whole gait signals show a great potential to serve as biomarkers of increased fall risk because they consider both inter-stride and intra-stride information of human gait cycles and are able to discriminate between different walking conditions. | en_US |
| dc.description.note | October 2019 | en_US |
| dc.identifier.citation | S. Ahmadi, C. Wu, N. Sepehri, A. Kantikar, M. Nankar, and T. Szturm, “The effects of aging and dual tasking on human gait complexity during treadmill walking: a comparative study using quantized dynamical entropy and sample entropy,” J. Biomech. Eng., vol. 140, no. 1, p. 011006, 2018 | en_US |
| dc.identifier.citation | S. Ahmadi, N. Sepehri, C. Wu, and T. Szturm, “Sample entropy of human gait center of pressure displacement: a systematic methodological analysis,” Entropy, vol. 20, no. 8, p. 579, 2018. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/34044 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | Entropy measures | en_US |
| dc.subject | Human gait | en_US |
| dc.subject | Dual-tasking | en_US |
| dc.subject | Fall risk | en_US |
| dc.title | On the use of sample entropy and quantized dynamical entropy of human gait signals as biomarkers of increased fall risk: experimental data analysis | en_US |
| dc.type | doctoral thesis | en_US |