High-intensity interval training (HIIT) is a form of training that has seen a rise in use in athletic and clinical populations (7,21,42). Specific HIIT programs can be developed by controlling variables such as the work and recovery intensities and durations, as well as the total number of intervals to be performed (5,26). Gibala et al. (19) have proposed using a 20-minute HIIT protocol consisting of 60 seconds of work interspersed with 60 seconds of recovery repeated for 10 repetitions (10 × 60 s:60 s). A rationale for this type of low-volume program was that the relative work interval intensities could be somewhat lower compared with those used during sprint interval-type training (8,18). Keeping the work intervals at somewhat lower intensities while extending their duration would make completing them more achievable while still being able to produce beneficial health-related adaptations for a wider range of individual capabilities. An additional advantage of the program was the reduced exercise time which could potentially increase program compliance. In studies incorporating the 10 × 60 s:60 s protocol (12,24,27), improvements in VO2max, muscle oxidative capacity, and insulin sensitivity were observed within a relatively short training period. Although the studies used different work and recovery intensities in their training protocols, a commonality among them was the use of lower extremity cycling as the mode of training.
Compared with lower extremity training, upper extremity low-volume HIIT training has received relatively little attention. Previous research pertaining to upper extremity exercise has primarily focused on areas such as the acute physiological effects of arm testing protocols (31), the effects of continuous training (CT) on cardiopulmonary function (35), and the transferability of adaptations between arm and leg training (16,34). Studies involving wheelchair-bound individuals have attempted to incorporate upper extremity interval training; however, the work and recovery intervals used in those studies tended to be of lower intensity and longer duration compared with HIIT studies involving able-bodied individuals (44).
The recent evolution and accessibility of arm ergometer equipment to the public have increased the popularity of upper extremity exercise. For individuals with lower extremity physical limitations or those who participate in activities emphasizing the musculature of the arms and torso, upper extremity interval training may be the modality of choice for improving cardiopulmonary fitness and muscular endurance. Therefore, the purpose of this study was to compare the physiological effects of an upper extremity, low-volume HIIT program to CT. It was hypothesized that upper extremity HIIT incorporating a 10 × 60 s:60 s protocol would result in greater improvements in cardiopulmonary fitness when compared with CT performed with a similar duration, frequency, and average training intensity.
Experimental Approach to the Problem
To date, relatively little research has focused on the effects of upper extremity HIIT. A 10 × 60 s:60 s HIIT protocol was selected for this study because of its purported advantages (19). The primary dependent measures used to evaluate training-related adaptations included peak oxygen uptake (VO2peak), peak heart rate (HRpeak), blood lactate concentration ([bLa]), peak power output (PPO), total exercise time (TET), and rating of perceived exertion (RPE). Work interval intensities were established based on a percentage of HRpeak derived from the arm crank graded exercise test (GXT) (%aHRpeak). Complete rest was selected for use during the recovery intervals because the equipment used during training did not provide visual feedback in the form of load, power output, or cadence, and it allowed for the standardization of effort during the recovery intervals for participants within the HIIT group. By using a combination of work and recovery intensities based on a %aHRpeak, it was possible to design an interval program that yielded an average training intensity similar to that of the CT group. By using similar average training intensities for the CT and HIIT groups and keeping the HIIT recovery intervals passive, the effects of peak training intensity could be compared with those of average training intensity. With this approach, it was possible to determine which of these intensity-related factors was responsible for contributing to the development of adaptations resulting from training.
Twenty healthy, low to moderately active college-aged students (13 women, 7 men) ranging in age from 20 to 33 years ( ± s.d. = 23.1 ± 2.8 years) volunteered for the study. Each participant signed a written informed consent document describing the protocols and risks associated with the experiment before its start. Participants initially completed health history and physical activity readiness questionnaires (PAR-Q) for selection and screening purposes. All protocols were approved by the California State University Long Beach Institutional Review Board for the Protection of Human Subjects before commencement of the study.
Participants were alternately assigned to either the CT (CT; 7 women, 3 men, n = 10) or HIIT group (6 women, 4 men, n = 10) as they entered the study until the number needed for each group was reached. None of the participants were experienced with the use of arm ergometry and were not engaged in any upper extremity endurance-type training before the start of the study. Participants were instructed to withhold initiation of any extraneous physical training once being admitted into the study. Instructions regarding diet, fluid intake, and activity levels were given before the GXTs as well as for individual training sessions. Participants were requested to refrain from any upper or lower extremity exercise for at least 24 hours before the GXT and to maintain normal eating and drinking patterns. In addition, caffeine-containing food or drink was prohibited for at least 4 hours before testing or training during the course of the study.
Anthropometric measurements including body mass and height were made using a calibrated medical scale and stadiometer. Body composition was determined by whole-body plethysmography (BOD POD; Cosmed, Concord, CA, USA). Calibration was performed before each test according to manufacturer's specifications. All participants performed pretraining and posttraining upper extremity GXTs. The tests were carried out using a Scifit Pro 1 upper body arm ergometer (Scifit, Tulsa, OK, USA). The ergometer had the capability to maintain a constant power output with variations in crank arm cadence. Participants were measured for headstock, handle, and seat positioning and were allowed to crank on the device to insure proper positioning before the pretraining GXT. These same measurements were then used in the posttraining GXTs.
Each GXT started with a 5-minute warm-up period performed at a power output of 10 W and a crank cadence ≥50 revolutions per minute (RPM). Once the warm-up was completed, power output was increased to 20 W and then incremented at a rate of 10 W·min−1 up to 50 W for women and 20 W·min−1 up to 60 W for men. When women reached 50 W, the power output was then increased by 5 W·min−1. For men, 10 W·min−1 increments were made once 60 W was reached. Criteria for test termination included the observation of a plateau in VO2 (<150 ml·min−1 with an increase in work rate), a drop in cadence below 50 RPM, signs and symptoms of exercise intolerance, or volitional fatigue.
Gas exchange and ventilation measurements used for the determination of oxygen uptake (VO2) were made with a Vacumed metabolic measurement system (Vacumed, Ventura, CA, USA). The gas analyzers were calibrated before every test using known gas concentrations (16% O2/4% CO2) and ambient air. A 3-L syringe was used to calibrate the turbine flow meter. The technical error of measurement (%TEM) for repeated measurements using the system was 4.0%. The highest value obtained during the test was determined to be the peak oxygen uptake (VO2peak). Peak power output was established as the power output achieved at VO2peak. Each participant wore a Polar (Polar Electro Inc., Lake Success, NY, USA) chest strap to transmit heart rate (HR) to the metabolic measurement system. The highest HR value obtained during the GXT was designated as the peak heart rate (aHRpeak). The %TEM for HR measurements was 4.1%.
Blood lactate concentrations ([bLa]) were measured using a finger-stick method (38). Samples were obtained at rest ([bLa]pre) just before the start of the GXT, at 50 W for women and 70 W for men ([bLa]mid), and immediately after the GXT ([bLa]post). During the 50 and 70 W stages, participants were instructed to drop an arm to the side while continuing to crank with the other. Cadence was allowed to drop below 50 RPM during this period of time. A blood sample was then obtained from a fingertip of the nonexercising hand. The stage was extended from 1 to 2 minutes to facilitate blood sampling and to give participants time to re-establish the required cranking cadence of ≥50 RPM. A Lactate Plus portable lactate analyzer (Nova Biomedical, Waltham, MA, USA), calibrated before each GXT, was used for the measurements. The %TEM for high and low lactate controls were 1.5 and 2.4%, respectively. Ratings of perceived exertion were obtained each minute during the GXT using the Borg 6–20 scale (6).
Three to 5 days after the pretraining GXT, the CT and HIIT groups began training. The total time for each training session was 30 minutes and consisted of 5 minutes of warm-up, 20 minutes of either CT or HIIT, and a 5-minute cool-down period. Both the warm-up and cool-down periods were performed at a self-selected intensity. Training sessions were performed 2 d·wk−1 for 6 consecutive weeks yielding a total of 12 training sessions. An upper extremity arm-cranking device known as the Krankcycle (Matrix, Cottage Grove, WI, USA) (Figure 1) was used for training. The Krankcycle has independent crank arms with a rotatable headstock that allows an individual to crank with both arms in parallel (double position) or in 180-degree opposition (split position) in either a clockwise or counter-clockwise direction. All activity was performed in a seated position with the crank arms rotating in a clockwise direction. Participants had the option to work between a double or a split position; however, most training was performed in a split position to more closely replicate the movement pattern used on the Scifit Pro 1 for testing. Based on initial pilot work, an average exercise intensity of approximately 80% aHRpeak was chosen for the 2 groups. This meant that the CT group exercised at the prescribed constant intensity for the 20 minutes training session. To achieve a similar average training intensity and duration as the CT group, the HIIT group performed 10, 60 seconds work intervals at approximately 90% aHRpeak. Each work interval was followed by 60 seconds of passive recovery.
Heart rate and RPE were monitored and recorded throughout the individual training sessions to gauge exercise intensity. Each session was supervised by the primary investigator who, along with the participant, was provided with continuous visual feedback of the HR response. This was accomplished using an Activio wireless HR monitoring system (Activio AB, Stockholm, Sweden). As training progressed, participants adjusted resistance or cadence on the Krankcycle to stay at the appropriate %aHRpeak during the individual training sessions. After the 6-week training protocol, participants were then retested within 1 week on the Scifit Pro 1 ergometer using the identical pretraining GXT protocol.
Minitab version 16 (Minitab, Inc. State College, PA, USA) and data from Currie et al. (12) were used to estimate sample size. A minimum of 9 subjects was sufficient to detect a within-group difference of 4.7 ml·min−1·kg−1 on the primary outcome measure of VO2peak with 80% power and a type I error rate of α = 0.05. The Statistical Package for Social Sciences (SPSS v.21; IBM Corporation, Armonk, NY, USA) was used for all subsequent data analyses. Multivariate analysis of variance was used to compare pretraining data between groups. Repeated-measures analysis of variance was used to evaluate within-group differences as a consequence of training. Analysis of covariance, using training group as the main factor and the respective pretraining measurement as a covariate, was used to compare between group differences in posttraining scores. A probability level of p ≤ 0.05 was used to determine statistical significance. Effect sizes were estimated using partial eta squared (). The magnitude of the effect size was considered either small (0.01 ≤ < 0.06), medium (0.06 ≤ < 0.14), or large ( ≥ 0.14) as proposed by Cohen (11).
All participants completed the 12 required training sessions. A summary of the physical characteristics and results of the pretraining and posttraining GXTs for both training groups are shown in Tables 1 and 2. No differences in pretraining age, body mass, height, or percentage body fat were found between groups (p ≥ 0.05). Body mass and percentage body fat were not changed in either group nor were any differences for either variable noted between groups after training (p ≥ 0.05).
Figure 2 displays the session by session HR response for each group. The mean training HR averaged across all sessions for the CT group was 81.9 ± 2.2% aHRpeak as established from the GXT and was consistent across training sessions (p = 0.405, = 0.104). Within the HIIT group, HR tended to decline as training progressed (p = 0.028, = 0.237) from a mean of 84.5 ± 3.0% aHRpeak recorded during the first session to a value of 82.0 ± 2.2% measured during the last training session. The mean training HR during the HIIT sessions was 82.6 ± 1.5% aHRpeak and not different (p = 0.365, = 0.046) from CT. The mean peak HR for the HIIT sessions was 92.3 ± 1.0% aHRpeak during the work intervals and did not significantly change with training (p = 0.517, = 0.087). The mean % aHRpeak during the passive recovery intervals was 73.0 ± 4.0% and tended to decline as training progressed (p = 0.001, = 0.348). With regard to RPE, no differences existed across training sessions for either the CT (p = 0.302, = 0.124) or HIIT group (p = 0.169, = 0.172) (Figure 3). When averaged across sessions, the overall mean training RPE for CT ( = 12.8 ± 0.6) was lower than that observed for the HIIT group ( = 13.8 ± 0.8) (p = 0.006, = 0.348).
No pretraining differences between groups were observed for VO2peak expressed as either ml·min−1·kg−1 (p = 0.101, = 0.142) or L·min−1 (p = 0.240, = 0.076), aHRpeak (p = 0.119, = 0.130), PPO (p = 0.269, = 0.067), RPEpeak (p = 0.322, = 0.054), [bLa]pre (p = 0.918, = 0.001), [bLa]mid (p = 0.551, = 0.020), [bLa]post (p = 0.118, = 0.130), or TET (p = 0.395, = 0.041). Seven of 10 participants increased VO2peak after CT. However, the average improvement tended to be small. Expressed in relative terms, the mean increase in VO2peak was 1.1 ml·min−1·kg−1 (95% confidence interval [CI]: −0.5 to 2.7 ml·min−1·kg−1) and not considered to be significant (p = 0.195). Expressed in absolute terms the mean difference in VO2peak was 0.1 L·min−1 (95% CI: −0.1 to 0.2 L·min−1) and was also not significantly affected (p = 0.140). Improvements in PPO and TET were seen after training. The mean increase in PPO was 7.0 W (95% CI: 3.5–10.5 W) (p = 0.001), whereas TET improved by 1.0 minutes (95% CI: 0.3–1.7 minutes) (p = 0.008). A mean decrease in RPEpeak of 0.9 units (95% CI: 0.04–1.7) (p = 0.041) was observed during the posttraining GXT. Neither aHRpeak (p = 0.622) nor [bLa]pre (p = 0.555), [bLa]mid (p = 0.767), and [bLa]post (p = 0.281) seemed to change as a result of training.
High-intensity interval training produced an increase in VO2peak in all 10 participants. The mean relative VO2peak increased by 4.8 ml·min−1·kg−1 (95% CI: 2.6–7.0 ml·min−1·kg−1) (p = 0.001), whereas absolute VO2peak increased by 0.3 L·min−1 (95% CI: 0.2–0.4 L·min−1) (p = 0.001). Peak power output increased by 12.0 W (95% CI: 5.4–18.6 W) (p = 0.003) as did TET by 2.2 minutes (95% CI: 1.4–3.0 minutes) (p = 0.0002). The aHRpeak increased by 5.2 b·min−1 (95% CI: 1.5–8.9 b·min−1) (p = 0.011), but RPEpeak (p = 0.383) was not changed. Blood lactate concentrations, [bLa]pre (p = 0.239), [bLa]mid (p = 0.109), and [bLa]post (p = 0.085), were not significantly affected by the HIIT protocol.
Analysis of covariance revealed several posttraining differences between CT and HIIT (Figure 4). VO2peak expressed as either ml·min−1·kg−1 (p = 0.007, = 0.358) or L·min−1 (p = 0.007, = 0.354) was found to be higher in the HIIT group after training by 4.1 ml·min−1·kg−1 (95% CI: 1.3–6.9 ml·min−1·kg−1) and 0.25 L·min−1 (95% CI: 0.1–0.4 L·min−1), respectively. Total exercise time was also found to be longer in the HIIT group by 1.4 minutes (95% CI: 0.4–2.3 minutes) (p = 0.008, = 0.349). However, no differences between groups were found for aHRpeak (p = 0.101, = 0.151), PPO (p = 0.305, = 0.062), RPE (p = 0.411, = 0.040), [bLa]pre (p = 571, = 0.018), [bLa]mid (p = 0.728, = 0.007), or [bLa]post (p = 0.083, = 0.167).
The primary finding of this study was that participation in a low-volume, upper extremity 10 × 60 s:60 s HIIT program resulted in greater relative improvement of VO2peak (∼14%) when compared with a CT group (∼4%) operating at a similar average training intensity. However, the amount of improvement observed in the HIIT group was less ( = 4.8 ml·min−1·kg−1; [95% CI: ± 2.2 ml·min−1·kg−1]) than what has been found in previous investigations using lower extremity HIIT protocols ( = 5.5 ml·min−1·kg−1; [95% CI: ±1.2 ml·min−1·kg−1]) (29). On an absolute basis, VO2peak increased in the HIIT group by 0.30 L·min−1 (95% CI: 0.18–0.41 L·min−1), whereas the CT group showed little change ( = 0.07 L·min−1 [95% CI: −0.06 to 0.20 L·min−1]). A recent meta-analysis (3) of lower extremity HIIT found programs lasting from 6 to 13 weeks using work:recovery ratios of ≥1:1 with a minimum 60 seconds work and 60 seconds recovery and frequencies of ≥ 3 d·wk−1 produced an average absolute increase in VO2max of 0.51 L·min−1 (95% CI: 0.43–0.60 L·min−1). One possible explanation for the observed difference in the amount of improvement of VO2peak between the current and previous studies may be that less muscle mass was used during upper extremity cranking when compared with participation in lower extremity activities (10,25). Generally speaking arm work results in VO2max values that are approximately 70–75% of those observed for leg work (33,40). Calbet et al. (9) found that performance of arm work resulted in a lower muscle O2 extraction capacity compared with leg work which could help explain the observed lower O2 uptakes. Furthermore, individuals who habitually train with the upper extremities tend to have lower VO2max values compared with those who train using activities emphasizing the lower extremities such as running or cycling (4,28). Besides differences in the use of upper vs. lower extremities, comparison of the current results to previous studies is confounded by factors such as variations in training frequency, training session duration and study length, differences in the specific components of the interval program, and the health and fitness status of the participants. Because of the practicalities of the training design and equipment used in this experiment, %aHRpeak and RPE were used to monitor training intensity rather than a measure such as %VO2max. Franklin (16) suggested that within a HR range of 70–85% of maximum arm effort, individuals would operate at approximately 57–78% of the arm VO2peak. In the current study, the average intensities for the CT and HIIT groups were 81.9 ± 2.2% and 82.6 ± 1.5% of aHRpeak, respectively, which would place them at the upper end of the cited range for arm VO2peak. However, while group training HR values were similar, group training VO2 values may have been different which could potentially produce different training outcomes and further complicate comparison to previous studies. With regard to fitness status, no participant in either group of the current study had previous training experience with upper extremity cranking activity. It is thought that individuals who are not specifically trained can potentially make greater gains in VO2max than those who would be considered more fit (2,29,41). In the current study, there did not seem to be a relationship (r = 0.088, p = 0.711) between an individual's initial level of fitness, as measured by VO2peak, and the amount of improvement made. The results suggest that the lack of upper extremity fitness did not have an appreciable effect on VO2peak, otherwise greater improvement would have been expected, particularly in the CT group.
Compared with the HIIT group, the CT group showed little improvement in VO2peak. It is possible that the training intensity, in combination with the relatively short training session duration and the smaller muscle mass used for arm cranking, did not produce a sufficient stimulus to elicit central adaptations that could lead to improvements in VO2peak.
Previous upper extremity training studies using CT have demonstrated improved cardiopulmonary fitness and performance that are of similar magnitude to leg training. For example, Turner et al. (39) found significant improvements in VO2max (7.0 ± 2.0 ml·min−1·kg−1) and PPO (59.0 ± 7 weeks) after 6 weeks of training (30 minutes per session·5 d·wk−1). An interesting observation was that muscle volume increased in the arms but not the legs, suggesting different mechanisms of adaptation. However, the program was performed at end-exercise intensities nearing maximal HR and had a higher overall training volume compared with the current study. The HIIT group in the current study was working at ∼92% aHRpeak during the 60-second work intervals which represented ∼66% (64–69%) of estimated peak leg values. By working at the higher intensity, participants in the HIIT group were likely activating more muscle mass compared with the CT group which may have been enough to exceed a threshold stimulus necessary to produce the observed improvements. Results from previous studies have shown that lower extremity interval training tended to produce both central and peripheral adaptations, whereas CT primarily resulted in the development of peripheral adaptations (13,14). Although in the current study no difference in aHRpeak was found between the 2 groups as a result of training, it was increased in the HIIT but not the CT group. The higher aHRpeak may have resulted in an improved peak cardiac output which could potentially contribute to the higher VO2peak (VO2peak = Qpeak·Δ arteriovenous O2 differencepeak) observed in the HIIT group.
Unlike VO2peak, PPO and TET were improved in both groups after training, but only TET was different between the 2. This may have been a consequence of the development of peripheral adaptations associated with improved aerobic metabolism. In lower extremity HIIT studies using a 10 × 60 s:60 s format, peripheral adaptations such as increased mitochondrial capacity and insulin sensitivity have been shown to occur in sedentary adults (24) and those with type II diabetes mellitus (27) working at intensities ranging from 60% PPO up to 95% PPO. In addition, it has been shown that peripheral adaptations can be developed without necessarily affecting VO2max while still being able to improve muscular endurance, PPO, and TET (23,30). With regard to blood lactate concentrations, there did not seem to be a difference between groups with respect to [bLamid] and [bLapost] in the current study. These results are consistent with Helgerud et al. (22) who did not find any significant change in the lactate threshold as a result of HIIT training.
Previous HIIT studies have raised questions regarding the most effective ways to control intensity and duration to produce specific training outcomes (7,36,37,43). It is generally accepted that, up to a point, training at higher intensities produces greater improvement in aerobic adaptations (22,41,43). For continuous activities, this intensity is typically considered to be the average %HRmax or %VO2max maintained during a training session. Because of the oscillatory nature of interval training, consideration should also be given to peak and average peak intensities as well as the amount of time spent at them when evaluating factors responsible for producing training effects (15). In the current study, both groups were training at similar average intensities. If the average training intensity was the primary factor responsible for the observed improvements, then it would have been expected to see similar outcomes in both groups. However, the HIIT group improved VO2peak and TET to a greater extent, suggesting that the higher average peak intensity of the work intervals was primarily responsible for producing the differences observed between the 2 groups. These results are in agreement with Gorostiaga et al. (20) who found that participants who trained with a 30 s·30 s−1 lower extremity HIIT protocol at ∼70% VO2max for 30 minutes per session improved VO2max and exercise capacity to a greater extent than a group training continuously using a similar intensity and duration. On the other hand, Overend et al. (32) did not see any advantage to either low- or high-power interval training when compared with CT whereas training at similar average intensities (80% VO2max) suggesting that intensity and quantity of work were more important for improving VO2max than the type of protocol used. These results do not rule out the possibility that an interaction between the average and peak intensities may have contributed to the observed improvements as seen currently.
Another finding of the study was that HIIT group improvements were made despite its low volume when compared with traditional continuous aerobic-based training programs. The training frequency in the current study was only 2·wk−1, whereas the American College of Sports Medicine recommends a minimum frequency of 3 sessions per week for aerobic-type activities (17). Still it is possible to see improvements in aerobic capacity with training frequencies lower than what has been recommended. Wenger and Bell (41) found that a training frequency as low as 2 d·wk−1 can produce improvements in VO2max in individuals who are considered less fit. Because none of the participants had previous upper extremity training experience, it would be reasonable to expect some improvement in VO2peak for both training groups. However, as with the initial level of fitness and average training intensity, the CT group showed little improvement. The weekly total training time for both groups of 60 min·wk−1, which includes the warm-up and cool-down periods, was well below the recommended minimum threshold of 75 min·wk−1 for aerobic-based programs (1). This would also help explain the relatively small improvements observed in the CT group and would again suggest the importance of the average peak training intensity for stimulating the training-related adaptations observed in the HIIT group. In this study, the CT protocol was used as a control where duration, frequency, and intensity and length of the training program were the same as that used by in the HIIT protocol. Little improvement was seen after CT suggesting that it was not a sufficient training stimulus to produce significant cardiopulmonary training adaptations, most likely a result of the low-volume nature of the program. The greater overall improvements made by the HIIT group for the same amount of training time as the CT group would indicate that it was more time efficient. This result is in agreement with previous studies involving low-volume training using the lower extremities (12,19,27).
Results from this study suggest that a 10 × 60 s:60 s upper extremity HIIT program is an effective means for improving measures of cardiopulmonary capacity and exercise time in individuals who are inexperienced with upper extremity cranking activity. Despite a program that used the upper extremities and one that would be considered low volume, significant improvements in VO2peak, PPO, and TET were obtained with relatively little time investment. Although the CT and HIIT groups were training at similar average intensities and CT showed improvement in PPO and TET, HIIT produced a better overall outcome. From a practical standpoint, the results would suggest that for interval-based programs the average exercise intensity, as commonly displayed on many HR monitoring systems as %HRmax, and the average peak training intensity, which is not generally provided by these systems, should be taken into consideration when evaluating their contributions in producing training adaptations. Given the constraints of the 10 × 60 s:60 s protocol as used in this experiment, it seemed that incorporating an average peak work interval intensity of approximately 90% aHRpeak combined with a passive recovery interval repeated 10 times was sufficient to produce positive results. The program was well tolerated by all participants and could be useful for individuals with limited use of their lower extremities or for those who want to incorporate upper extremity training into their overall programs.
The authors thank the dedicated group of participants who volunteered their time and effort to allow this research to be made possible. The results of this present study do not constitute endorsement of any product by the authors or the National Strength and Conditioning Association. The authors have no conflicts of interest to disclose.
1. American College of Sports Medicine. ACSM's Guidelines for Exercise Testing and Prescription (9th ed.). Pescatello LS, Arena R, Riebe D, Thompson PD, eds. Baltimore, MD: Lippincott Williams & Wilkins, 2014. pp. 19–38, 175.
2. Astrand PO, Rodahl K. Textbook of Work Physiology (3rd ed.). New York, NY: McGraw-Hill, 1986. pp. 420.
3. Bacon AP, Carter RE, Ogle EA, Joyner MJ. VO2max
trainability and high intensity interval training in humans: A meta-analysis. PLoS One 8: 1–6, 2013.
4. Barbier J, Lebiller E, Ville N, Rannou-Bekono F, Carré F. Relationships between sports-specific characteristics of athlete's heart and maximal oxygen uptake. Eur J Cardiovasc Prev Rehabil 13: 115–121, 2006.
5. BiIlat LV. Interval training for performance: A scientific and empirical practice. Part 1: Aerobic interval training. Sports Med 31: 13–31, 2001.
6. Borg GAV. Psychosocial bases of perceived exertion. Med Sci Sports Exerc 14: 377–381, 1982.
7. Buchheit M, Laursen PB. High-intensity interval training, solutions to the programming puzzle. Part I: Cardiopulmonary emphasis. Sports Med 43: 313–338, 2013.
8. Burgomaster KA, Howarth KR, Phillips SM, Rakobowchuk M, MacDonald MJ, McGee SL, Gibala MJ. Similar metabolic adaptations during exercise after low volume sprint interval and traditional endurance training in humans. J Physiol 586: 151–160, 2008.
9. Calbet JA, Holmberg HC, Rosdahl H, Van Hall G, Jensen-Urstad M, Saltin B. Why do arms extract less oxygen than legs during exercise? Amer J Physiol 289: R1448–R1458, 2005.
10. Clausen JP. Effect of physical training on cardiovascular adjustments to exercise in man. Physiol Rev 57: 779–815, 1977.
11. Cohen J. Statistical Power Analysis for the Behavioral Sciences (2nd ed.). New York, NY: LEA Publishers, 1988. p. 274.
12. Currie KD, Dubberly JB, McKelvie RS, MacDonald MJ. Low-volume, high intensity interval training in patients with CAD. Med Sci Sports Exerc 45: 1436–1442, 2013.
13. Daussin FN, Ponsot E, Dufour SP, Lonsdorfer-Wolf E, Doutreleau S, Geny B, Piquard F, Richard R. Improvement VO2max
by cardiac output and oxygen extraction adaptation during intermittent versus continuous endurance training. Eur J Appl Physiol 101: 377–383, 2007.
14. Daussin FN, Zoll J, Dufour SP, Ponsot E, Lonsdorfer-Wolf E, Doutreleau S, Mettauer B, Piquard F, Geny B, Richard R. Effect of interval versus continuous training on cardiorespiratory and mitochondrial functions: Relationship to aerobic performance improvements in sedentary subjects. Amer J Physiol 295: R264–R272, 2008.
15. Demarie S, Koralsztein JP, Billat V. Time limit and time at VO2MAX
during a continuous and intermittent run. J Sports Med Phys Fitness 40: 96–102, 2000.
16. Franklin BA. Aerobic exercise training programs for the upper body. Med Sci Sports Exerc 21(Suppl 5): S141–S148, 1989.
17. Garber CE, Blissmer B, Deschenes MR, Franklin BA, Lamonte MJ, Lee IM, Nieman DC, Swain DP. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Med Sci Sports Exerc 43: 1334–1359, 2011.
18. Gibala MJ, Little JP, Van Essen M, Wilkin GP, Burgomaster KA, Safdar A, Raha S, Tarnopolsky MA. Short-term sprint interval versus traditional endurance training: Similar initial adaptations in human skeletal muscle and exercise performance. J Physiol 575: 901–911, 2006.
19. Gibala MJ, Little JP, MacDonald MJ, Hawley JA. Physiological adaptations to low-volume, high-intensity interval training in health and disease. J Physiol 590: 1077–1084, 2012.
20. Gorostiaga EM, Walter CB, Foster C, Hickson RC. Uniqueness of interval and continuous training at the same maintained exercise intensity. Eur J Appl Physiol 63: 101–107, 1991.
21. Guiraud T, Nigam A, Gremeaux V, Meyer P, Juneau M, Bosquet L. High-intensity interval training in cardiac rehabilitation. Sports Med 42: 587–605, 2012.
22. Helgerud J, Hoydal K, Wang E, Karlsen T, Berg P, Bjerkaas M, Simonsen T, Helgesen C, Hjorth N, Bach R, Hoff J. Aerobic high-intensity intervals improve VO2max
more than moderate training. Med Sci Sports Exerc 39: 665–671, 2007.
23. Henriksson J, Reitman JS. Quantitative measures of enzyme activities in type I and type II muscle fibres of man after training. Acta Physiol Scand 97: 392–397, 1976.
24. Hood MS, Little JP, Tarnopolsky MA, Myslik F, Gibala MJ. Low-volume interval training improves muscle oxidative capacity in sedentary adults. Med Sci Sports Exerc 43: 1849–1856, 2011.
25. Jondeau G, Katz SD, Zohman L, Goldberger M, McCarthy M, Bourdarias JP, LeJemtel TH. Active skeletal muscle mass and cardiopulmonary reserve. Failure to attain peak aerobic capacity during maximal bicycle exercise in patients with severe congestive heart failure. Circulation 86: 1351–1356, 1992.
26. Laursen PB, Jenkins DG. The scientific basis for high-intensity interval training. Sports Med 32: 53–73, 2002.
27. Little JP, Gillen JB, Percival ME, Safdar A, Tarnopolsky MA, Punthakee Z, Jung ME, Gibala MJ. Low-volume high-intensity interval training reduces hyperglycemia and increases muscle mitochondrial capacity in patients with type 2 diabetes. J Appl Physiol 111: 1554–1560, 2011.
28. Michael JS, Rooney KB, Smith R. The metabolic demands of kayaking: A review. J Sports Sci Med 7: 1–7, 2008.
29. Milanović Z, Sporiš G, Weston M. Effectiveness of high-intensity interval training (HIT) and continuous endurance training for VO2max
improvements: A systematic review and meta-analysis of controlled trials. Sports Med 45: 1469–1481, 2015.
30. Örlander J, Kiessling KH, Karlsson J, Ekblom B. Low intensity training, inactivity and resumed training in sedentary men. Acta Physiol Scand 101: 351–362, 1977.
31. Orr JL, Williamson P, Anderson W, Ross R, McCafferty S, Fettes P. Cardiopulmonary exercise testing: Arm crank vs cycle ergometry. Anaesthesia 68: 497–501, 2013.
32. Overend TJ, Paterson DH, Cunningham DA. The effect of interval and continuous training on the aerobic parameters. Can J Sport Sci 17: 129–134, 1992.
33. Pendergast DR. Cardiovascular, respiratory, and metabolic responses to upper body exercise. Med Sci Sports Exerc 21(5 Suppl): S121–S125, 1989.
34. Pogliaghi S, Terziotti P, Cevese A, Balestreri F, Schena F. Adaptations to endurance training in the healthy elderly: Arm cranking versus leg cycling. Eur J Appl Physiol 97: 723–731, 2006.
35. Price DT, Davidoff R, Balady GJ. Comparison of cardiovascular adaptations to long-term arm and leg exercise in wheelchair athletes versus long-distance runners. Am J Cardiol 85: 996–1001, 2000.
36. Rozenek R, Salassi JW III, Pinto NM, Fleming J. Acute cardiopulmonary and metabolic responses to high-intensity interval training (HIIT) protocols using 60s of work and 60s recovery. J Strength Cond Res 30: 3014–3023, 2016.
37. Seiler S, Jøranson K, Olesen BV, Hetlelid KJ. Adaptations to aerobic interval training: Interactive effects of exercise intensity and total work duration. Scand J Med Sci Sports 23: 74–83, 2013.
38. Tietz NW. Textbook of Clinical Chemistry. Philadelphia, PA: Saunders, 1986. p. 483.
39. Turner DL, Hoppeler H, Claassen H, Vock P, Kayser B, Schena F, Ferretti G. Effects of endurance training on oxidative capacity and structural composition of human arm and leg muscles. Acta Physiol Scand 161: 459–464, 1997.
40. Van Loan MD, McCluer S, Loftin JM, Boileau RA. Comparison of physiological responses to maximal arm exercise among able-bodied, paraplegics and quadriplegics. Paraplegia 25: 397–405, 1987.
41. Wenger HA, Bell GJ. The interactions of intensity, frequency and duration of exercise training in altering cardiorespiratory fitness. Sports Med 3: 346–356, 1986.
42. Weston KS, Wisloff U, Coombes JS. High-intensity interval training in patients with lifestyle-induced cardiometabolic disease: A systematic review and meta-analyses. Br J Sports Med 48: 1227–1234, 2014.
43. Wisløff U, Ellingsen Ø, Kemi OJ. High-intensity interval training to maximize cardiac benefits of exercise training? Exerc Sport Sci Rev 37: 139–146, 2009.
44. Zwinkels M, Verschuren O, Janssen TW, Ketelaar M, Takken T. Exercise training programs to improve hand rim wheelchair propulsion capacity: A systematic review. Clin Rehabil 28: 847–861, 2014.