The purpose of the study was to compare the effects of a feedback-controlled treadmill (FeedbackTM) to a traditional fixed-speed treadmill (FixedTM) on spatiotemporal gait means, variability, and dynamics. The study also examined inter-session reliability when using the FeedbackTM. Ten young adults walked on the FeedbackTM for a 5-minute familiarization followed by a 16-minute experimental trial. They returned within one week and completed a 5minute familiarization followed by a 16-minute experimental trial each for FeedbackTM and FixedTM conditions. Mean walking speed and step time, length, width, and speed means and coefficient of variation were calculated from all experimental conditions. Step time, length, width, and speed gait dynamics were analyzed using detrended fluctuation analysis. Mean differences between experimental trials were determined using ANOVAs and reliability between FeedbackTM sessions was determined by intraclass correlation coefficient. No difference was found in mean walking speed nor spatiotemporal variables, with the exception of step width, between the experimental trials. All mean spatiotemporal variables demonstrated good to excellent reliability between sessions, while coefficient of variation was not reliable. Gait dynamics of step time, length, width, and speed were significantly more persistent during the FeedbackTM condition compared to FixedTM, especially step speed. However, gait dynamics demonstrated fair to poor reliability between FeedbackTM sessions. When walking on the FeedbackTM, users maintain a consistent set point, yet the gait dynamics around the mean are different when compared to walking on a FixedTM. In addition, spatiotemporal gait dynamics and variability may not be consistent across separate days when using the FeedbackTM.
The reliability of the treadmill belt speed using a feedback-controlled treadmill algorithm was analyzed in this study. Using biomechanical factors of the participant’s walking behavior, an estimated walking speed was calculated and used to adjust the speed of the treadmill. Our proposed algorithm expands on the current hypotheses of feedback-controlled treadmill algorithms and is presented below. Nine healthy, young adults walked on a treadmill controlled by the algorithm for three trials over two days. Each participant walked on the feedback-controlled treadmill for one 16-minute and one five-minute trial during day one and one 16-minute trial during day two. Mean, standard deviation, interclass correlation coefficient (ICC), and standard error of measurement (SEM) were analyzed on the treadmill belt speed mean, standard deviation, and coefficient of variation. There were significantly high ICC for mean treadmill speed within- and between-days. Treadmill speed standard deviation and coefficient of variation were significantly reliable within-day. These results suggest the algorithm will reliably produce the same treadmill belt speed mean, but may only produce a similar treadmill belt speed standard deviation and coefficient of variation if the trials are performed in the same day. A feedback-controlled treadmill algorithm that accounts for the user’s behavior provides a greater level of control and minimizes any possible constraints of walking on a conventional treadmill.
Aims:Coupling between walking and breathing in humans is well established. In healthy systems, the ability to couple and uncouple leads to energy economization. It is unknown if physiologic efficiency is susceptible to alteration, particularly in individuals with airflow obstruction. The aim of this research was to determine if coupling was compromised in a disease characterized by abnormal airflow and dyspnoea, and if this was associated with reduced energy efficiency. Methods: As a model of airflow obstruction, 17 chronic obstructive pulmonary disease (COPD) patients and 23 control subjects were included and walked on a treadmill for 6 minutes at three speeds (preferred speed and ±20% preferred speed) while energy expenditure, breathing, and walking were recorded. Rating of perceived exertion was recorded at the end of each walking trial. The most commonly used frequency ratio (ie, strides:breath) and cross recurrence quantification analysis were used to quantify coupling. Linear regression models were used to determine associations. Results: Less complex frequency ratios, simpler ratios, (ie, 1:1 and 3:2) accompanied with stronger coupling were moderately associated with increased energy expenditure in COPD subjects. This was found for all three speeds. Conclusion: The novel finding was that increased energy expenditure was associated with stronger and less complex coupling. Increased effort is needed when utilizing a frequency ratio of 1:1 or 3:2. The more stable the coupling, the more effort it takes to walk. In contrast to the complex energy efficient coupling of controls, those with airflow obstruction manifested simpler and stronger coupling associated with reduced energy efficiency. K E Y W O R D Scost of transport, entrainment, locomotor respiratory coupling, recurrence quantification analysis, VO2
Sports medicine research is a developing field which uses a processed combination of videos, force data, and accelerometer data. In radiology data is processed within the radiology workflow before being stored in PACS. Both processed and raw data can be uploaded to a central database. Currently, in the biomechanics workflow this data must be processed by researchers on local computers. There is currently no centralized method to process this data, each researcher must use unique scripts which require specific computer environments. Also, once data has been stored in a central database there is no method to query that data for further processing. Processed data is a valuable tool for researchers to educate athletes and coaches. Therefore, there is a need for a central, standardized system which can process data within the biomechanics workflow. The integrated biomechanics informatics system (IBIS) is an ideal choice for this system as it already provides a centralized database used by biomechanics researchers. Using an imaging-informatics approach we have developed a web application which allows users to query, retrieve, and process data on the IBIS system. The web application's efficacy will be measured by testing expert and novice users on the speed and ease of using the web application and comparing the results of web processing to local processing. In the future this web application can be extended to host multiple types of biomechanics data processing on the IBIS system.
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