Tai Chi, Physiological Complexity, and Healthy Aging - Gait

Abstract

This dataset contains gait and electromyography (EMG) data collected during a hybrid study that included a two-arm randomized clinical trial (RCT) along with an additional observational comparison group. The RCT arm investigated the short-term effects of a Tai Chi intervention on 60 Tai Chi healthy naïve subjects, aged 50-79 years, living within the Greater Boston area, and reporting no regular Tai Chi practice within the past 5 years. Subjects were either randomized to 6 months of Tai Chi or usual care. Subjects came in for a baseline visit along with 3 month and 6 month follow-ups. The observational comparison group consisted of 27 healthy Tai Chi experts, aged 50-79 years, currently engaged in an active Tai Chi training regimen, each with at least 5 years of Tai Chi experience. The expert group was tested only at their baseline visit. The gait and EMG data were simultaneously recorded during walking at the subjects preferred speed for 10 minutes under the single-task condition and for 90 seconds under the dual-task condition. Our aim for this study was to use gait and EMG data to gain a better understanding of the mobility changes associated with Tai Chi training.

Background

Previous studies have shown the beneficial effects of Tai Chi on falls [1-4], balance [1, 5-8], and gait [9-11]. Some evidence suggests that the beneficial effect of Tai Chi on mobility may be more pronounced under cognitive dual-task conditions, such as performing serial subtractions while walking [11-12].

Gait stride time variability (calculated from stride to stride intervals) and speed are established measures of mobility health [13-15].  Complexity based metrics such as detrended fluctuation analysis have shown promise for assessing mobility health but have not been widely used to assess changes in gait due to Tai Chi training [16-17]. The collection of 10 minutes of gait data (under the single-task condition) is enough for the computation of detrended fluctuation analysis which can reveal long-term memory effects across the span of hundreds of strides [16].

Additionally, few studies have investigated the muscle activation patterns associated with Tai Chi training in an effort to understand the mechanisms behind Tai Chi’s effects on mobility. Muscle co-contraction measured using electromyography (EMG), and defined as the simultaneous activation of agonist and antagonist muscle groups, can serve as an informative clinical marker of mobility health [18]. The data from this project allows for exploration of whether co-contraction of muscle groups in the lower extremities may be an underlying mechanism associated with mobility improvements from Tai Chi training.

Methods

This project contains gait and electromyography (EMG) data from a hybrid study that included a two-arm randomized clinical trial (RCT) along with an additional observational comparison group. The RCT arm investigated the short-term effects of a Tai Chi intervention on 60 Tai Chi healthy naïve subjects, aged 50-79 years, living within the Greater Boston area, and reporting no regular Tai Chi practice within the past 5 years. Subjects were either randomized to 6 months of Tai Chi or usual care. Subjects came in for a baseline visit along with 3 month and 6 month follow-ups. The observational comparison group consisted of 27 healthy Tai Chi experts, aged 50-79 years, currently engaged in an active Tai Chi training regimen, each with at least 5 years of Tai Chi experience. The expert group was tested only at their baseline visit. The gait and EMG data were simultaneously recorded during walking at the subjects preferred speed for 10 minutes under the single-task condition and for 90 seconds under the dual-task condition.

To collect gait stride-to-stride timing information, wireless force-sensitive resistor footswitches were placed under the subject’s toes and heels to record toe and heel strikes. This gait data was collected with the ME6000 (Mega Elektronika, Inc) data acquisition monitor. Data was recorded for 10 minutes while walking normally (single-task) and for 90 seconds while walking and performing verbalized serial subtractions (dual-task). Gait speed was calculated based on the distance the subjects walked over a given period of time (10 minutes or 90 seconds). Surface EMG of the anterior tibialis and lateral gastrocnemius muscles was recorded simultaneously with the gait data. The EMG data was collected with a Noraxon data acquisition system (Noraxon, Scottsdale, USA) with the selectable low pass filter set to 500Hz. The EMG and gait footswitch data were both sampled at 1500Hz.

The Institutional Review Boards at Beth Israel Deaconess Medical Center and Brigham and Women’s Hospital, Boston, Massachusetts, approved this study. The randomized clinical trial was registered at ClinicalTrials.gov (NCT01340365).

Data Description

The files are split by task, with the files under the Single-task folder containing data from 10 minutes of normal walking and the files under the Dual-task folder containing 90 seconds of walking while performing serial subtractions by 3. The data files are provided in standard WFDB format, named:

SXXX_KT_VY(_PZ) - for non-experts

SXXX_KT_master(_PZ) - for experts

where XXX is the subject number, K is S for the single-task (ST) recording and D for the dual-task (DT) recording, Y is the visit number, and Z is the recording part for instances that had to be recorded in two segments.

Group allocation by Subject ID with age, gender, education, body mass index (BMI), visit, trail making time, category fluency, hallway length, number of laps, and distance walked, can be found in the accompanying file: TCPCHA_Subjects.csv.

Usage Notes

A previous publication used detrended fluctuation analysis to investigate the long-range scaling in gait stride times [19]. This study employed intention to treat analysis and included all of the single-task gait data provided here. Information on detrended fluctuation analysis along with code can found here: https://www.physionet.org/content/dfa/1.0.0/.

Another study analyzed co-contraction from electromyography data and stride time variability and gait speed under single- and dual-task conditions [in-press].  This publication didn't include subjects who were: lost to follow up (5 non-experts), missing EMG data (4 non-experts), or had corrupt footswitch data (2 non-experts). See the EMG_Subset.csv file for the subjects included in the analysis for this publication.

Both of these studies made cross-sectional comparisons between Tai Chi experts and Tai Chi naive subjects at their baseline visit along with comparisons between the naive subjects randomized to Tai Chi training versus usual care. Additional insight into the effects of Tai Chi training may be garnered by using other analysis techniques on this gait and electromyography data. The recordings are at the original sampling rate of 1500 Hz but can downsampled as appropriate. 

Release Notes

This updated release includes the 90 seconds of walking data collected when subjects were performing a dual-task (serial subtractions).  This release also includes the electromyography (EMG) data collected during the single- and dual-task walking.

Acknowledgements

We thank Jacquelyn Walsh, Matthew Lough, Danielle Berkowitz and Mary Quilty for research assistance.

Conflicts of Interest

Peter Wayne is the founder and sole owner of the Tree of Life Tai Chi Center. Peter Wayne's interests were reviewed and managed by the Brigham and Women's Hospital and Partner's HealthCare in accordance with their conflict of interest policies. The other author(s) have no conflicts of interest to declare.

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