Author: | Andrea Ancillao | ISBN: | 9783319674377 |
Publisher: | Springer International Publishing | Publication: | October 24, 2017 |
Imprint: | Springer | Language: | English |
Author: | Andrea Ancillao |
ISBN: | 9783319674377 |
Publisher: | Springer International Publishing |
Publication: | October 24, 2017 |
Imprint: | Springer |
Language: | English |
This book reviews in detail the history of motion analysis, including the earliest attempts to capture, freeze, study and reproduce motion. The state-of-the-art technology in use today, i.e. optoelectronic systems, is then discussed, as motion capture now plays an important role in clinical decisions regarding the diagnosis and treatment of motor pathologies from the perspective of evidence based medicine. After reviewing previous experiments, the book discusses two modern research projects, providing detailed descriptions of the methods used and the challenges that arose in the context of designing the experiments. In these projects, advanced signal processing and motion capture techniques were employed in order to design: (i) a protocolĀ for the validation and quality assurance of clinical strength measurements; (ii) an algorithm for interpreting clinical gait analysis data; and (iii) a number of user-friendly software tools that can be used in clinical settings to process dat
a and to aggregate the results into reports. In closing, a thorough discussion of the results is presented from a contextual standpoint.
This book reviews in detail the history of motion analysis, including the earliest attempts to capture, freeze, study and reproduce motion. The state-of-the-art technology in use today, i.e. optoelectronic systems, is then discussed, as motion capture now plays an important role in clinical decisions regarding the diagnosis and treatment of motor pathologies from the perspective of evidence based medicine. After reviewing previous experiments, the book discusses two modern research projects, providing detailed descriptions of the methods used and the challenges that arose in the context of designing the experiments. In these projects, advanced signal processing and motion capture techniques were employed in order to design: (i) a protocolĀ for the validation and quality assurance of clinical strength measurements; (ii) an algorithm for interpreting clinical gait analysis data; and (iii) a number of user-friendly software tools that can be used in clinical settings to process dat
a and to aggregate the results into reports. In closing, a thorough discussion of the results is presented from a contextual standpoint.