Both raw and filtered accelerometer data were graphically displayed to compare and contrast the 2 datasets for each of the 14 trials. Although visual inspection of the graphs revealed no discernible differences, a Pearson product-moment correlation coefficient was calculated to determine the specific relationship within each trial for the raw and filtered accelerometer data (Microsoft Office Excel 2003, Redmond, Wash).
For all 14 trials, the derived acceleration data were then graphically displayed with both raw and filtered accelerometer data. Again, visual inspection showed close agreement between all 3 (raw acceleration, smoothed/filtered acceleration from the accelerometer, and smoothed/filtered acceleration from video) datasets. Correlation analyses were performed to determine the relationship between the derived acceleration data with the raw accelerometer data.
An example of the results of the graphic comparison between raw and filtered accelerometer data is depicted in Figure 8. Although this graph represents data for only one trial for one subject, a similar pattern was observed for all other trials.
The comparison between accelerometer raw data and filtered data showed a correlation coefficient of r = 0.99 for all 14 trials (see Table 1). On the basis of these results, raw datasets from the accelerometer were then selected for comparison with the acceleration data obtained from the kinematic analysis of barbell movement captured by high-speed video.
A typical graphic comparison between raw and filtered accelerometer data and the corresponding acceleration data obtained in the kinematic analysis is presented in Figure 9. In all of the other trials, graphs showed the corresponding acceleration datasets displaying a similar curve.
Results of the correlation analyses show a high positive relationship between the accelerometer raw data and the derived acceleration data from kinematic analysis. Correlation coefficient values ranged from r = 0.94 to 0.99 for all subjects across 2 trials (see Table 2). All relationships between raw accelerometer data and the corresponding acceleration data obtained from the kinematic analysis were statistically significant (r = 0.87, p < 0.01). Because the level of weightlifting experience among participants was varied, the acceleration profiles were considered to be dependent on each subject's strength and technique.
The objective of this study was to validate data collected from an accelerometer with acceleration data derived from a kinematic analysis of a movement sequence recorded by high-speed video. The results show that the accelerometer displayed nearly identical acceleration values compared with the derived acceleration values and support the hypothesis that a strong positive relationship existed between the 2 datasets. This inexpensive, commercially available accelerometer has demonstrated the capability to collect valid barbell acceleration values during a high-pull movement sequence.
The accelerometer was shown to be an instrumentation device that could easily be attached to a barbell. The required laptop computer running the acquisition software was easily positioned so as to provide little if any distraction to the subjects during their lifting trials. Thus, neither subjects nor their equipment were encumbered by cables attaching sensors to a data acquisition unit or laptop computer. Additionally, the sensors and software required a minimum time for setup in data collection sessions. Most importantly, the instrument provided immediate results and feedback of movement performance.
Current literature in weightlifting describes key components of weightlifting from both the kinematic and kinetic perspectives (2,3,5-14). Although past studies have identified biomechanical characteristics of weightlifting techniques, none of the data were collected in real time during training sessions (3,5,6,7-11,13). In additional pilot work, the accelerometer was actually attached to the barbell of several weightlifters during training sessions to identify the barbell vertical acceleration patterns of their Olympic lifts with various workloads. The data were ready to display immediately after each trial for quick feedback to coaches and athletes; data collected after the catch phase were ignored.
During pilot sessions, acceleration patterns for various athletes were shown to change during the course of a training session, with patterns generally reflecting lower acceleration values. This decrease in barbell acceleration may be related to fatigue. Instead of using the method of deciding on the training volume before the particular training session, this instrument may lead to determination of an optimal range of training loads for the individual lifters during the actual training session. Training load could be based on the performance that the athlete displays for any given day on a lift-to-lift basis. Only one study was found that analyzed fatigue trends in weightlifting, but the data were collected in a laboratory setting (7). The accelerometer may ultimately be found to be a simpler, more economical way to collect relevant data about workloads that can be used in a real-world weightlifting training venue.
There are some limitations in using the accelerometer. First, there is the need for “line-of-sight” between the sensor and receiver for wireless operation. At the time of data collection, distance between the accelerometer and the laptop was approximately 3 m. This distance was similar during pilot work in the weightlifting room. The connection was not lost within approximately 30 m; thus, distance between the accelerometer and the receiver is not thought to be a serious constraint.
The second limitation is the durability of the accelerometer. Ultimately, the accelerometer needs to provide meaningful, relevant, and accurate information that impacts performance enhancement while being used within the confines of a realistic weightlifting training session. Initially, the need for validating this unit was for the expressed purpose of being able to measure barbell acceleration patterns during Olympic lifts.
However, the accelerometer was not designed or developed for the purpose of absorbing the shock of being dropped onto a lifting platform from the height of a barbell raised overhead by a weightlifter. Excessive external shock not only interferes with the acceleration reading, but, in certain situations, it may also destroy the device. If there is a possibility of external shock to the accelerometer, an adequate amount of protection is needed to ensure its viability. This need eventually led to the design of the mounting foam unit shown in Figure 10. Subsequent pilot testing demonstrated that this padded mount provided sufficient protection for the accelerometer.
The final and most relevant limitation was that the individual (X, Y, and Z) acceleration data were directionally dependent. As stated earlier, this property of the accelerometer unit prevented the collection and analysis of barbell vertical acceleration data during the execution of snatch lifts. Because rotation of the bar in the “catch” phase caused the accelerometer to change its position from the initial vertical orientation, it became necessary to use the high-pull motion for validating the vertical acceleration pattern.
As previously mentioned, the collection of barbell acceleration data and subsequent assessment have not been well studied (6,7). Because acceleration patterns directly mirror force production, they may be useful in understanding the differences in lifting technique that occur not only within a training session but also over multiple training sessions. The possibility of determining the number of sets, repetitions, and workload for a training session based on information directly related to performance and fatigue/nonfatigue status needs to be explored. In summary, the use of an accelerometer that is easily attached to a barbell and that provides real-time results needs further study to determine its usefulness.
Because of its capability for capturing data and real-time display, this commercial accelerometer could be a valuable tool for field application. Because the unit collects data that reflect force production for lifting during a training session, is easily attached, leaves the athlete unrestrained by cables, and is not cost-prohibitive, it seems worthwhile to study its potential for improving lifting performance.
By quantifying barbell acceleration during training sessions, an accelerometer was considered a valuable tool during our work with athletes and coaches. When there was a change or decline in barbell acceleration during the high-workload sessions, the pattern was immediately observable; the information gained gave both the coach and lifter the opportunity to consider whether the workload needed to be adjusted or terminated. Use of an accelerometer as a fatigue indicator may be helpful in detecting the early signs of fatigue. The findings of Haff et al. (7) show that an adequate amount of rest between repetitions prevented decreases in barbell velocity when compared with a condition of no rest between lifts. Because it is important to have an adequate amount of rest between sets to fully recover, any disparity within the measured acceleration patterns for the total number of repetitions within a set was clearly shown. Whether within a single workout or over multiple training sessions, knowledge of changes in lifting acceleration patterns can be of benefit to athletes and coaches. The potential for quantifying workout volume comes closer to being a reality.
In summary, wherever force production is required to initiate any sport motion, acceleration patterns and values are critical to describing and understanding the movement. By measuring this aspect of the sporting activity, athletes may improve their performances on the basis of scientific information rather than on time-consuming trial and error.
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Keywords:© 2009 National Strength and Conditioning Association
barbell acceleration; barbell movement; resistance training