CN110141204A - A method of selection velocity profile horses - Google Patents
A method of selection velocity profile horses Download PDFInfo
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- CN110141204A CN110141204A CN201910367632.4A CN201910367632A CN110141204A CN 110141204 A CN110141204 A CN 110141204A CN 201910367632 A CN201910367632 A CN 201910367632A CN 110141204 A CN110141204 A CN 110141204A
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- horses
- heart rate
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- velocity profile
- rate variability
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02405—Determining heart rate variability
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B69/00—Training appliances or apparatus for special sports
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/40—Animals
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2244/00—Sports without balls
- A63B2244/24—Horse riding
Abstract
The present invention provides a kind of methods for selecting velocity profile horses, it is characterized in that, the following steps are included: 1) heart rate variability metrics of the measurement field under pre-games rest state, wherein the heart rate variability metrics include: R -- R interval standard deviation, R-R interval average value standard deviation, adjacent interphase difference > 50ms percentage；2) according to the heart rate variability data of step 1) horses, the horses for selecting the percentage of the R -- R interval standard deviation, R-R interval average value standard deviation, adjacent interphase difference > 50ms relatively high carry out the match of 2000m or less speed, and selection selection R -- R interval standard deviation, R-R interval average value standard deviation, the horses that the percentage of adjacent interphase difference > 50ms is relatively low participate in the match of 2000m or more speed.The above method can reflect the excellent of horses locomitivity to a certain extent, and the judgement for the state that can also be raced to horses pre-games is provided fundamental basis.
Description
Technical field
The invention belongs to technical field of livestock husbandry, and in particular to a method of selection velocity profile horses.
Background technique
As people's lifestyle changes, the exchange and interdynamic of material and culture are more frequent, horse racing gradually with Humanistic Factors
Ingenious to be combined into together, it is leading for being gradually changed by traditional horse racing with amusement and leisure, and melt body is educated, entertained
Modern show jumping competition and popularized.The universal requirement for causing people to horses special project performance of show jumping competition improves, thus
Horses selection is particularly important.
Analyze the otherness of horses static state heart rate variability metrics and blood gas index, the phase of more each index and contest used time
Guan Xing, the characteristics of probing into each index, provide theoretical foundation for the selection of velocity profile horses.
Summary of the invention
Technical problem to be solved by the invention is to provide a kind of methods for selecting velocity profile horses, to horses figure knot
The monitoring of structure, gender, heart rate variability can reflect the excellent of horses locomitivity to a certain extent, can also match to horses
The judgement of the state of preceding sports is provided fundamental basis.
To achieve the goals above, the technical solution used in the present invention is: a kind of method for selecting velocity profile horses, packet
Include following steps:
1) heart rate variability (HRV) index of measurement field under pre-games rest state；
2) according to the heart rate variability data of step 1) horses, the horses for selecting the heart rate variability data relatively high into
The following speed match of row 2000m, the horses for selecting the heart rate variability data relatively low participate in the match of 2000m or more speed.
Based on the above technical solution, the present invention can also have following further specific choice or optimum choice.
Specifically, the acquisition method of heart rate variability metrics described in step 2) is that heart rate receiver is mounted on the horses heart
Dirty corresponding sites are collected data.
Specifically, heart rate variability described in step 2) (HRV) index includes: between R -- R interval standard deviation (SDNN), R-R
Every one or more of average value standard deviation (RMSSD) and the percentage (pNN50) of adjacent interphase difference > 50ms.
Specifically, it is rapid 2) described in heart rate variability metrics further include low frequency power high frequency power ratio (LF/HF), selection
The higher horses competition of low frequency power high frequency power ratio (LF/HF).
Specifically, it is rapid 2) described in heart rate variability metrics further include low-frequency standard value (LFnu), select the low frequency mark
The lower horses competition of quasi- value (LFnu).
Specifically, it is rapid 2) described in heart rate variability metrics further include adjacent R-R interphase average value (MeanRR), the average heart
Rate (MeanHR), very low frequencies power (VLF), low frequency power (VF), high frequency power (HF), total frequency (TP), high-frequency standard value
(HFnu), all standard deviation (SD1) of normal R-R interval and all normal R-R interval standard deviation (SD2).
Specifically, the pre-games rest state refers to that horses are placed in horse circle, and it is in quiet, without human interference, body
In the state that the heart loosens.
Specifically, the time of measuring of heart rate variability metrics continues 20-60mins.Preferably, heart rate variability metrics
Time of measuring continues 30mins.
It should be noted that carry out multiple indexs and meanwhile compare be in order to verify mutually, can obtain more accurately as a result,
Detection can be re-started when inconsistent or with reference to indexs such as test result or appearances.
Compared with prior art, the beneficial effects of the present invention are: using horses pre-games HRV index and horses pre-games speed
It is matched, to can be used as by more full and accurate data according to leg velocity profile horse in addition to the direct result of test event performance
It is selected, so that it is guaranteed that it is more accurate to select horse racing, is performed better than.
Specific embodiment
For a better understanding of the present invention, the content that the present invention is furture elucidated combined with specific embodiments below, but this hair
Bright content is not limited solely to the following examples.
Embodiment:
Test apparatus
POLAR EQUINE V800 heart rate monitor: it is a to have GPS function to can detect horse that Finland, which produces POLAR V800 heart rate monitor,
Travelling route, records the detection device of horses heart rate and heart rate variability in real time, which records by Bluetooth wireless transmission.
Finish Lynx terminal timing: horses achievement can be accurate to signa by the system, accurately record horse
Contest result.
Kubios HRV software: being researched and developed by external Healtech S.A., which is suitable for clinical research and animal health,
Have the function of that analysis checks autonomic nerves system, HRV data can be analyzed, analysis content includes time domain variable, frequency domain
Variable and non-linear variable.
This experiment is mainly using heart rate spectra and heart rate variability under Polar table acquisition field pre-games rest state
Indices, data acquisition after import Kubios HRV software analyzed, calculated, finally obtain required HRV time domain index,
Frequency-domain index and nonlinear indicator.
Test environment
Horses are led into the quiet environments such as Ma Quan before horses competition, and send out special messenger keep an eye on ensure horses be in it is quiet,
No human interference, body and mind carry out the acquisition of heart rate variability data in the state of loosening.
Test Data Collecting and index determining
Heart rate variability metrics (HRV): every field measures 30min heart rate spectra and the heart under pre-games rest state
Rate variability (HRV) index, comprising: adjacent R-R interphase average value (MeanRR), R -- R interval standard deviation (SDNN), average heart rate
(MeanHR), percentage (pNN50), the very low frequencies function of R-R interval average value standard deviation (RMSSD), adjacent interphase difference > 50ms
Rate (VLF), low frequency power (VF), high frequency power (HF), low frequency power high frequency power ratio (LF/HF), total frequency (TP), low frequency mark
Quasi- value (LFnu), high-frequency standard value (HFnu), all standard deviation (SD1) of normal R-R interval and whole normal R-R interval standards
Poor (SD2).
Contest result: heart rate variability metrics allow horses normally to take in competition after acquiring, and with emphasis timekeeping system essence
Really record horses competition time.
Test grouping
Horses are grouped according to the event that horses are participated in, event has 1000m speed to match, 1600m speed is matched,
The match of 3600m speed and the match of 5000m speed.The field of each project is divided into three groups according to competition time, it is respectively outstanding
Group, good group and general group.
Table 2-1 is grouped situation
Note: significant difference (P < 0.05) between different lowercases of going together；Extremely significant (the P of difference between different capitalizations
< 0.01)；Similarly hereinafter.
Statistical analysis
R-R spacing data is acquired with Polar table, heart rate variability metrics are handled using Kubios HRV software
Analysis obtains each achievement data of heart rate variability frequency domain；Arrangement statistics is carried out to data with EXCEL；It is used with SPSS19.0 software
One-way analysis of variance compares between each group that index error is anisotropic, filters out and does phase with achievement after the HRV index with achievement close relation
The Pearson bivariate analysis of closing property.As a result it is shown in the form of means standard deviation.As a result as follows:
1000m speed matches HRV indicator difference between field each group
As shown in Table 2 between 1000m speed match field each group static state HRV index as seen from table otherness are as follows: when HRV
Outstanding group of horses of SDNN are substantially less than common group (P < 0.05) in the index of domain, and have raising trend by outstanding group to common group；
Outstanding group of RMSSD extremely significant lower than medium group and common group (P < 0.01), and medium group of RMSSD value is maximum；Outstanding group of NN50 value
It is substantially less than medium group (P < 0.05), extremely significant to be lower than common group (P < 0.01)；Outstanding group of pNN50 value is substantially less than medium group
With common group (P < 0.05), and medium group of pNN50 value be three groups between it is maximum.
In frequency-domain index, outstanding group of LF/HF ratio is significantly higher than medium group and common group (P < 0.05)；Outstanding group of LFnu
It is significantly higher than medium group (P < 0.05)；Outstanding group of HFnu is substantially less than medium group (P < 0.05).VLF is by outstanding group to common group
There is decreasing trend but difference is not significant (P > 0.05)；HF has raising trend but not significant (the P > of difference by outstanding group to common group
0.05)。
Each group difference of SD1, SD2 is not significant (P > 0.05) in nonlinear indicator, but SD1 is by outstanding group to common group
There is raising trend.
2 1000m speed of table matches otherness between HRV each group
1000m speed matches each index of field static state HRV and with competition time does correlation it is as shown in the table as shown in Table 3:
Static each index of HRV and achievement correlation results are shown are as follows: in time domain index it is relevant to competition time have RMSSD, NN50,
Pnn50, wherein RMSSD and pNN50 and competition time are in significant positive correlation (P < 0.05), and NN50 is with competition time in extremely significant
It is positively correlated (P < 0.01).It is relevant to the contest used time in frequency-domain index to have LF/HF, LFnu, HFnu, wherein contest used time and LF/
HF, LFnu are in significant negatively correlated (P < 0.05), with HFnu in significant negatively correlated (P < 0.05).In nonlinear indicator SD1 with it is competing
The used time is matched in significant positive correlation (P < 0.05).
Mean HR and Mean RR is in extremely significant negatively correlated (P < 0.01) in HRV index；RMSSD and HR is in significant negative
It closes (P < 0.01)；NN50 and RMSSD is in extremely significant positive correlation (P < 0.01)；PNN50 and Mean RR, NN50 in it is extremely significant just
Related (P < 0.01), with Mean HR in extremely significant negatively correlated (P < 0.01)；LF/HF and VLF is in extremely significant positive correlation (P <
0.01), with HF in significant negatively correlated (P < 0.05)；TP and VLF, LF are in extremely significant positive correlation (P < 0.01), are manifested with LF/HF
It writes and is positively correlated (P < 0.05)；LFnu and HF is in extremely significant positive correlation (P < with LF/HF in extremely significant negatively correlated (P < 0.01)
0.01)；HFnu and HF is in extremely significant positive correlation (P < 0.01), with LF/HF, LFnu in extremely significant negatively correlated (P < 0.01)；SD1
It is in extremely significant positive correlation (P < 0.01) with SDNN, NN50, pNN50；SD2 and SDNN, SD1 are in extremely significant positive correlation (P <
0.01), (P < 0.05) is positively correlated in significant with TP.
The 3 index related table of 1000m speed horse racing pre-games HRV of table
1600m speed matches HRV indicator difference between field each group
As shown in Table 4, the difference of static state HRV index between the horses each group that participation 1000m speed is matched are as follows: HRV time domain index
Outstanding group of middle SDNN is extremely significant to be lower than medium group (P < 0.01), substantially less than plain edition (P < 0.05), and medium group significantly high
In common group (P < 0.05)；Outstanding group of extremely significant lower than medium group (P < 0.01), substantially less than common group of (P < in RMSSD
0.05)；Outstanding group of pNN50 extremely significant lower than medium group (P < 0.01), substantially less than common group (P < 0.05).
In frequency-domain index in VLF outstanding group be substantially less than medium group (P < 0.05)；Outstanding group extremely significant it is higher than in LFnu
Etc. groups (P < 0.01), substantially less than common group (P < 0.05)；In HFnu outstanding group it is extremely significant be lower than medium group (P < 0.01),
Substantially less than common group (P < 0.05).
4 1600m speed of table matches otherness between HRV each group
By doing correlation analysis to 1600 meters of speed horse racing each indexs of static state HRV of participation and competition time, as a result such as
Table 5, static each index of HRV and achievement correlation results are shown are as follows: SDNN and competition time are positively correlated in significant in time domain index
(P < 0.05)；LF/HF, LFnu and competition time are in significant negatively correlated (P < 0.05), HFnu and competition time in frequency-domain index
(P < 0.05) is positively correlated in significant.
Mean HR and Mean RR is in extremely significant negatively correlated (P < 0.01) in HRV index；RMSSD and Mean RR is in significant
It is positively correlated (P < 0.05), is in extremely significant positive correlation (P < 0.01) with SDNN, with Mean HR in significant negatively correlated (P < 0.05)；
NN50 and RMSSD is in extremely significant positive correlation (P < 0.05)；PNN50 and Mean RR, SDNN are in significant positive correlation (P < 0.05),
It is in extremely significant positive correlation (P < 0.01) with RMSSD, NN50 with Mean HR in significant negatively correlated (P < 0.05)；VLF and SDNN
It is positively correlated (P < 0.05) in significant, is in extremely significant positive correlation (P < 0.01) with pNN50；LF is manifested with SDNN, NN50, pNN50
It writes and is positively correlated (P < 0.05), be in extremely significant positive correlation (P < 0.01) with VLF；HF and RMSSD is positively correlated (P < in significant
0.05)；TP and SDNN, RMSSD are in extremely significant positive correlation (P < 0.01) with VLF, LF, HF in significant positive correlation (P < 0.05)；
LFnu and HF is in extremely significant positive correlation (P < 0.01) with LF/HF in extremely significant negatively correlated (P < 0.01)；HFnu and HF is in extremely aobvious
It writes and is positively correlated (P < 0.01), with LF/HF, LFnu in extremely significant negatively correlated (P < 0.01)；SD1 and SDNN, RMSSD, NN50,
LF, HF, TP are in extremely significant positive correlation (P < 0.01)；SD2 and SDNN, LF, HF, TP, SD1 are in extremely significant positive correlation (P <
0.01), (P < 0.05) is positively correlated in significant with NN50, VLF, RMSSD.
The 5 index related table of 1600m speed horse racing pre-games HRV of table
3600m speed matches HRV indicator difference between field each group
By table 2-6 it is found that participating in the difference of static state HRV index between the horses each group that 3600m speed is matched are as follows: outstanding group of SDNN
It is extremely significant to be greater than common group (P < 0.01)；PNN50 has significant difference (P < 0.05) between medium group and common group, and common
Group pNN50 is noticeably greater than outstanding group；Outstanding group of frequency-domain index HF is significantly higher than medium group (P < 0.05), and extremely significant higher than general
Logical group (P < 0.01)；Outstanding group of LF/HF value is in extremely significant difference (P < 0.01) with common group and outstanding group extremely significant lower than general
Logical group, outstanding group with medium group of significant difference (P < 0.05) and outstanding group is substantially less than medium group；Outstanding group of TP is in common group
Extremely significant difference (P < 0.01), outstanding group extremely significant lower than common group；Outstanding group of LFnu is in extremely significant difference (P < with common group
0.01) with medium group of significant difference (P < 0.05), outstanding group extremely significant lower than common group, substantially less than medium group；HFnu is outstanding
Group with commonly organize variant, and difference is extremely significant (P < 0.01), and outstanding group is extremely significant higher than common group, outstanding group with it is medium
It organizes significant difference (P < 0.05) and outstanding group is significantly higher than medium group.
6 3600m speed of table matches otherness between HRV each group
By the 3600m index related table 2-7 of speed horse racing pre-games HRV it is found that under horses pre-games 30min rest state
In the HRV index measured, LF/HF and contest used time are in extremely significant positive correlation (P < 0.01), i.e. LF/HF value bigger contest used time
Longer, then horses achievement is poorer；In significant positive correlation (P < 0.05), i.e. the LFnu value bigger contest used time is longer for LFnu and achievement,
Then horses achievement is poorer；HF, TP, HFnu and achievement are used in significant negatively correlated (P < 0.05) and the bigger contest of HF, TP, HFnu value
When it is fewer, then horses contest result is better.
Time domain index MeanRR, RMSSD and frequency-domain index LF and HF are positively correlated, and time domain index MeanRR, RMSSD with
HF is in extremely significant positive correlation (P < 0.01)；RMSSD, HF and LF/HF value are in significant negatively correlated (P < 0.05)；SDNN,RMSSD,
VLF, LF, HF and TP are in extremely significant positive correlation (P < 0.01)；HF and LFnu in extremely significant negatively correlated (P < 0.01), MeanHR with
LFnu negatively correlated (P < 0.05), LF/HF value and LFnu are in extremely significant positive correlation (P < 0.01)；HF and HFnu in it is extremely significant just
Related (P < 0.01), MeanHR and HFnu is positively correlated (P < 0.05) but correlation is not significant；LF/HF value, LFnu and HFnu
In extremely significant negatively correlated (P < 0.01).
The 7 index related table of 3600m speed horse racing pre-games HRV of table
5000m speed matches HRV indicator difference between field each group
By table 2-8 it is found that participating in the difference of static state HRV index between the horses each group that 5000m speed is matched are as follows: HRV time domain refers to
It is significantly higher than medium group, common group (P < 0.05) for outstanding group of SDNN in mark；Outstanding group of pNN50 is substantially less than medium group of (P <
0.05), substantially less than common group (P < 0.05).It is significantly higher than medium group (P < 0.05) for outstanding group of LF in frequency-domain index, significantly
Higher than common group (P < 0.05)；Outstanding group of LF/HF is significantly higher than medium group and common group (P < 0.05), and by outstanding group to general
Logical group reduces according to this；Outstanding group of LFnu is significantly higher than common group (P < 0.05)；Outstanding group of HFnu is substantially less than common group of (P <
0.05)。
8 5000m speed of table matches otherness between HRV each group
By doing correlation analysis to participation 5000m speed horse racing each index of static state HRV and competition time, as a result such as table
9, static each index of HRV and achievement correlation results are shown are as follows: SDNN and competition time are in significant negative correlation (P in time domain index
< 0.05), LF/HF and competition time are in significant negatively correlated (P < 0.05) in frequency-domain index；LFnu is with competition time in extremely significant
Negatively correlated (P < 0.01)；HFnu and contest used time are in extremely significant positive correlation (P < 0.01).
Mean HR and Mean RR is in extremely significant negatively correlated (P < 0.01) in HRV index, and pNN50 and Mean HR are in significant
Negatively correlated (P < 0.05)；LF and SDNN is in extremely significant positive correlation (P < 0.01), is positively correlated (P < 0.05) in significant with RMSSD；
LF/HF and SDNN is positively correlated (P < 0.05) in significant, is in extremely significant positive correlation (P < 0.01) with LF；LFnu and LF is in significantly just
Related (P < 0.05) is in extremely significant positive correlation (P < 0.01) with LF/HF with HF in significant negatively correlated (P < 0.05)；HFnu with
LF is positively correlated (P < 0.05) in significant in significant negatively correlated (P < 0.05), with HF, is in extremely significant negative correlation with LF/HF, LFnu
(P < 0.01).
The 9 index related table of 5000m speed horse racing pre-games HRV of table
The HRV index error opposite sex, HRV index and competition time correlation analysis obtain as follows between different way Yili horse each groups
Conclusion: horses sympathetic nerve under rest state is occupied an leading position, and the horses pre-games that parasympathetic nerve is suppressed has slightly
Tension, concentrate degree height, this short distance speed more demanding to horses explosive force and instantaneous velocity matches more advantageous, institute
With such horses 1000m, 1600m short distance speed match it is more advantageous, i.e., when horses are in a good state of health SDNN, RMSSD,
PNN50, HFnu value are lower, and the higher horses locomitivity of LF/HF ratio may be more preferable；Horses parasympathetic under rest state
Nerve is occupied an leading position, and horses decreased heart rate, delayed conduction can be caused, and is conducive to the reduction of horses pre-games energy consumption, allows horse
It being participated in match with more easily mood, this sports longer for way plays an important role, so 3600m,
5000m race horse SDNN, RMSSD, pNN50, TP higher, LFnu junior are more suitable for taking in competition.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (7)
1. a kind of method for selecting velocity profile horses, which comprises the following steps:
1) heart rate variability metrics of the measurement field under pre-games rest state；
2) according to the heart rate variability metrics of step 1) horses, the horses for selecting heart rate variability metrics relatively high are carried out
The match of 2000m or less speed, the horses for selecting heart rate variability metrics relatively low participate in the match of 2000m or more speed.
2. a kind of method for selecting velocity profile horses according to claim 1, it is characterised in that: heart rate described in step 2)
Variability metrics include in the percentage of R -- R interval standard deviation, R-R interval average value standard deviation and adjacent interphase difference > 50ms
It is one or more of.
3. a kind of method for selecting velocity profile horses according to claim 1, it is characterised in that: heart rate described in step 2)
The acquisition method of variability metrics is that heart rate receiver is mounted on sites corresponding to horses heart to be collected data.
4. it is according to claim 2 it is a kind of select velocity profile horses method, it is characterised in that: it is rapid 2) described in heart rate become
Anisotropic index further includes low frequency power high frequency power ratio, selects the higher horses ginseng of the low frequency power high frequency power ratio
Match.
5. it is according to claim 2 it is a kind of select velocity profile horses method, it is characterised in that: it is rapid 2) described in heart rate become
Anisotropic index further includes low-frequency standard value, selects the lower horses competition of the low-frequency standard value.
6. a kind of method for selecting velocity profile horses according to claim 1-5, it is characterised in that: heart rate variability
The time of measuring of property index continues 20-60mins.
7. a kind of method for selecting velocity profile horses according to claim 6, it is characterised in that: heart rate variability metrics
Time of measuring continues 30mins.
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Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108209902A (en) * | 2017-05-25 | 2018-06-29 | 深圳市未来健身衣科技有限公司 | Sportsman's competitive state appraisal procedure and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108209902A (en) * | 2017-05-25 | 2018-06-29 | 深圳市未来健身衣科技有限公司 | Sportsman's competitive state appraisal procedure and system |
Non-Patent Citations (2)
| Title |
|---|
| ALEX CLAIBORNE 等: ""Comparison of Heart Rate Variability in Intercollegiate Explosive Power vs. Sustained Power and Endurance Athletes", 《MEDICINE & SCIENCE IN SPORTS & EXERCISE》 * |
| 程洁 等: "采用心率变异性指标监控伊犁马热身效果及竞赛表现", 《新疆农业科学》 * |
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