Comparative analysis of physical load intensity in absolute and relative heart rate rates ​​using heart rate monitors

Фотографии: 

E.A. Vlasov
Professor, Dr.Med. V.Yu. Lebedinskiy
National Research Irkutsk State Technical University, Irkutsk

Keywords: heart rate monitor, heart rate, students, physical training, team system, telemetry, accelerometer.

Introduction. As of today, the search for the ways to strengthen health of children, adolescents and young people is one of the focus areas of science in the field of physical culture and sports, and for this purpose it is necessary to develop the most accurate and informative tool for monitoring the functional state of the given contingent. At the same time, the university system of physical education is in short supply of methods of in-depth integrated control over the exposure of physical exercises on the body of students during traditional Physical Education lessons, as opposed to the task-oriented examination of athletes conducted separately and in vitro [4].

One of the focus areas of the Scientific-Research Laboratory "Physical Health Monitoring" is biomedical support of the training process. In order to carry out the integrated control over the functional state of those involved in physical education, it is essential to use the methods of remote monitoring explicitly during the lessons [2, 3]. For that very reason we have purchased and are now successfully using the telemetry team system, which consists of 20 heart rate monitors working remotely and synchronously.

Objective of the study was to conduct a comparative analysis of the physical load intensity in absolute and relative values of heart rate (HR) using modern control methods.

Methods and structure of the study. Pulse is an indirect indicator of the body state. By its rate we can estimate load, recovery status, potential disease and general state of health. This method is very popular for it is easy enough to measure HR. Simple manual pulse measurement is often inaccurate due to some reasons: carelessness of students, lack of practical knowledge, etc. Moreover, such measurements are taken between exercises and do not always picture exactly the body reaction when performing the exercise.

At the same time, using the telemetry team system we can accurately analyze motor density of lessons, calculate average HR for a group at a certain moment of exercising or average HR for each student over the entire period of exercising, identify the fittest students and adjust the load for those who perform exercises with insufficient intensity.

Besides, the department specialists have developed a tool for analyzing the human body's response to physical load.

This is a percentage ratio of the HR at rest to the actual HR at a certain moment of exercising (Table 1) or to the average values HR over the entire period of exercising (could be a series of exercises, or a lesson as a whole).

Table 1. Absolute and relative values of HR during exercises of various intensity levels

Exercise

Students’ order numbers

1st

2nd

3rd

4th

5th

6th

7th

8th

9th

10th

11th

12th

13th

Average at rest

109

90

68

64

71

77

71

75

82

87

74

85

78

100

100

100

100

100

100

100

100

100

100

100

100

100

Average (step exercises)

146

117

102

112

108

120

121

101

119

140

111

119

107

134

130

150

175

152

156

170

135

146

161

151

140

138

Average (2km cross country race)

182

172

169

171

170

189

192

156

203

178

177

177

179

167

191

249

267

239

245

270

208

248

205

239

208

229

Average (recovery at the end of the lesson)

126

112

100

107

104

122

100

109

133

118

107

105

117

116

124

147

167

146

158

141

145

162

136

145

124

150

Average during the lesson

158

132

125

133

127

144

137

129

151

146

142

136

139

145

147

183

207

179

187

194

172

185

168

192

160

178

As part of this study, we conducted not the developmental or training session, but the diagnostic one, with the involvement of first-year male students, who fit into the first functional health group. During one lesson 13 students were subject to the functional test of 20 sit-ups and physical exercises of various intensity levels. In process, we did real-time measurements of the students’ cardiovascular system characteristics, followed by computer processing of the data obtained for each student: calculation of functional test results, determination of the peak HR values, average HR values during specific exercises, and assessment of relative values for each type of activity.

Results and discussion. The diagrams of the cardiovascular system reaction as a percentage of the resting state (Fig. 1) reveal some of its trends.

Fig. 1. Each student's pulsometry in relative values of HR

Thus, in the students with the low physical fitness level (high HR at rest) they become less pronounced and more smoothed at the level of 170%, while in those with the low HR at rest, on the contrary – reach 300% when exposed to physical load. However, there are students whose diagrams are in the upper lines both in absolute HR values and percentagewise (for instance, students #4, 11, and 13). Another interesting feature is that during strenuous physical loads its peak values are distributed with a greater gradation, as opposed to its absolute values, where, on the contrary, they are grouped at the level of the upper limits.

For better understanding of the lesson structure we recorded its chronometry: 0:00.00 - rest before the functional test; 0:03.10 - 20 sit-ups per 30 seconds; 0:04.00 - rest (recovery rate registration); 0:07.25 – step exercises; 0:12.31 – running in a line (two 400m laps); 0:17.08 - walking + breathing exercises; 0:18.31 - special running exercises (SRE); 0:20.46 - walking + breathing exercises; 0:23.28 – driving to acceleration for 40 m, two reps; 0:26.08 - general conditioning exercises (GCE); 0:34.07 - 2km cross country race (the following task was set: "To run two cross country laps (1 km) at comfortable speed"); 0:49.00 - breathing exercises; 0:54.29 – 400 m acceleration; 0:55.50 – low-intensity exercises and breathing exercises; 1:03.44 - end of the lesson.

The computer analysis of the functional test (Table 2) revealed that HR recovers in 1 minute only in two students (4th and 12th), in 1.5 minute – in seven students, and in 2 minutes and more – in six athletes (1st, 6th, 8th, 9th, 11th, and 13th) - low physical fitness level.

Table 2. Results of functional testing using modern HR monitoring methods and time of covering 2km race distance

 

Students’ order numbers

1st

2nd

3rd

4th

5th

6th

7th

8th

9th

10th

11th

12th

13th

HR at rest

109

90

68

64

71

77

71

75

82

87

74

85

78

HR after 20 sit-ups

152

127

126

130

129

131

148

125

144

143

142

138

129

HR increase in percent

39

41

85

103

82

70

108

67

76

64

92

62

65

Recovery time

3.00

1.25

1.18

0.58

1.34

2.24

1.30

2.10

1.49

1.39

2.15

1.00

1.53

Result of 2km run

13.09

10.21

10.09

12.18

09.49

10.35

10.28

11.50

09.56

13.28

13.58

11.34

12.42

 

Therefore, the average level of HR recovery in the group after 20 sit-ups per 30 seconds was 1 minute 45 seconds. Taking into consideration that the study involved healthy students with no significant functional abnormalities, and that the normal HR recovery rate for healthy untrained adolescents is up to 2 minutes [1, 6], they were proved to be healthy enough, but had a relatively low physical fitness level. The average heart rate increase after finishing the sit-ups exercises equals 74%, which corresponds to the upper limit of normal for healthy untrained adolescents. High values ​​of HR at rest are disturbing, thus, HR below 75 bpm is registered only in six students (3rd, 4th, 5th, 7th, 8th, 11th).

Fig. 2. Pulsometry in each student in absolute values of HR

Based on the 2km cross country race distance results (Table 2), the students were divided into two groups: the first one - less than 11 minutes (2nd, 3rd, 5th, 6th, 7th, 9th ) and second one – more than 11 minutes (1st, 4th, 8th, 10th, 11th, 12th, 13th). In the second group of students, the average HR was registered at the same level - 170-180 bpm. This suggests that students performed the exercise correctly (ran at high speed, with about 70% of the maximum capacity), while students of the first group had a substantial gap in their HR values, which is clearly seen in Figure 2 and Table 1. Accordingly, two sub-groups were formed based on these data: three students (6th, 7th, 9th) with the values of 189, 192 and 203, and three students (2nd, 3rd, 5th) with the values of 169, 170 and 172 bpm, respectively. According to the survey, it can be concluded that the first subgroup students (6th, 7th, 9th) had extremely low functional capabilities, and those of the second subgroup (2nd, 3rd, 5th) had high functional capabilities. The capabilities of the second group students (1st, 4th, 8th, 10th, 11th, 12th, 13th) were relatively average.

Conclusion. It was found that each study group attending each physical education lesson was made of three different categories of students. To improve the lesson efficiency it is necessary to comply with a certain gradation when dosing exercises both by volume and intensity. In this regard, we need to develop domestic (more affordable) prototypes of such command systems for monitoring the functional parameters and their full implementation explicitly in the university physical education process, and not only in elite athletic training.

References

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Abstract.
The article describes the results of the application of heart rate monitors in the physical education course, namely a command system that can record the heart rate of up to 20 people at a time. The study was conducted at the premises of the Physical Education Department of National Research Irkutsk State Technical University with the male students of the first functional health group. There was described a method of determining the functional capabilities of students at physical education lessons with the use of heart rate monitors. In addition, there were considered several methods of recording the intensity and impact of physical exercises on the student's body, and some regular human body's responses to physical exercises in case of using such a method were identified. Computer processing of the functional test (20 sit-ups) results was performed to determine the exact recovery time in seconds after a standard exercise.