Effects of synchronization between cardiac and locomotor rhythms on oxygen pulse during walking.

Author:Takeuchi, Shinta
Position:Research article - Report
 
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Introduction

When humans and other mammals rhythmically exercise, heartbeats interact with other biological rhythms or external rhythms, and synchronization between the heartbeat and the other rhythms is observed (Glass, 2001). Synchronization between the heartbeat and locomotor activity rhythms (cardiac-locomotor synchronization; CLS) occurs in humans during walking and running (Kirby et al., 1989; Niizeki et al., 1993, 1996; Nomura et al., 2001, 2003). CLS has been proposed to be an efficient phenomenon for exercising the body (Kirby et al., 1989; 1992) and is thought to optimize muscle blood flow and minimize cardiac afterload based on the hypothesis that peak intra-arterial pressure due to cardiac contraction occurs at the lowest phase of the intramuscular pressure cycle. CLS also increases stroke volume (SV) associated with increase in venous return by the Frank-Starling law based on the hypothesis that increase in venous return due to muscular pump action occurs during cardiac diastole. Increase in SV results from decrease in peripheral vascular resistance and changes in pressure in the ascending aorta caused by vertical body movement during running (O'Rourke and Avolio, 1992). In fact, Phillips et al. (2013) reported that CLS provided a performance improvement when running long distances. If CLS also has physiological significance for blood supply to muscles by cardiac contraction during walking, it could be applied to rehabilitation program for patients with depressed left ventricular ejection function and elderly people. However, few studies have reported the functional significance of CLS during walking (Niizeki and Saitoh, 2014).

The ratio between oxygen consumption (V[O.sub.2]) and heart rate (HR) defines the oxygen pulse ([O.sub.2] pulse), which is numerically equal to the product of SV and the arteriovenous oxygen difference (a-v[O.sub.2] difference), according to Fick's equation (Wasserman et al., 1999). [O.sub.2] pulse also independently predicts SV during submaximal exercise in healthy subjects (Bhambhani et al., 1994; Whipp et al., 1996). Therefore, we examined whether CLS has physiological significance for blood supply during walking, using [O.sub.2] pulse as an alternative SV index.

Methods

Subjects

Twelve healthy men (mean height: 169.4 cm, range: - 1.64.0-1.79 m; weight: 57.9 kg, range: 48.4-68.6 kg; age: 21.2 years, range: 19-25 years) with no history of cardiopulmonary diseases participated in this study (Table 1). Each subject provided an informed consent after being provided with a verbal explanation of the intent and the experimental procedures. This study protocol was approved by the Ethics Committee of the University. Physical activity as well as alcohol and caffeinated beverage consumption were prohibited 24 h before testing. Drinking and eating, except water, were also prohibited 3 h before testing.

Protocols

We determined each subject's treadmill load (treadmill speed and grade) at which their HR was maintained at approximately 120 beats per min (Table 1). Target heart rate was derived from the 50-70 percent of estimated maximal heart rate, which is formula of optimal heart rate during exercise for heart failure patients in Japan. Subjects walked on a treadmill (Autorunner AR-200, Minato Medical Science Co. Ltd, Osaka, Japan), and the treadmill speed was increased gradually in the range which subjects can walk (limited at 6.0 km/h). When the load was insufficient, the treadmill grade was increased until the target HR was achieved. The subjects walked at the determined treadmill speed and grade for at least 5 min to confirm the appropriate load.

The subjects then rested at least 15 min during which they were instrumented for data collection. Electrodes for electrocardiogram (ECG), a foot switch sensor, and a mask connected to an expired gas analyzer were placed on the chest, right heel, and face of the subjects, respectively. Thereafter, the subjects were instructed to conduct the two treadmill protocols in a random order. In the first protocol, subjects walked at the frequency of their HR to induce synchronization between heartbeat and locomotor activity (CLS protocol). In the other protocol, subjects walked at their preferred pace (free protocol as reference data). Both protocols were performed at the determined treadmill load for each subject for 20 min. First 10 min was warm-up period. Next 10 min was measurement period. The treadmill load (treadmill speed and grade) was fixed while each protocol. Therefore treadmill load and walking time were equal between the two protocols. Subjects rested in a sitting position for at least 15 min between the two protocols.

In the CLS protocol, firstly they walked at each treadmill load for 5 min. Next, they walked for 5 min with a buzzer signal, which was generated by an ECG monitor (Bedside monitor BSM-2400 series Life Scope 1, Nihon Kohden Corp., Tokyo, Japan). The buzzer sounded with the occurrence of each R waves, so subject's heart rate and the frequency of the buzzer were same. After their HR reached a steady state, they walked with a buzzer signal for 10 min. We collected data during the last 10 min of the synchronized walking period.

In the free protocol, firstly they walked at each treadmill load for 10min. Next, they walked at their preferred pace for 10 min. We collected data during the last 10 min of the preferred walking period. Because SV and the a-v[O.sub.2] difference vary between individuals, depending on the degree of obesity at rest and submaximal exercise (Vella et al., 2011), the value at rest was not appropriate to use as reference data. Thus, we set equal treadmill load and exercise time for both protocols.

Data collection

The R-R interval (RRI) was measured continuously from a surface ECG using standard bipolar leads (CM5). The ECG signal was amplified and filtered to distinguish the R waves of the QRS complex. We set the filtering frequency band to 10-300 Hz to avoid movement artifacts. The ECG signal was digitized with a sampling frequency of 1 kHz using a personal computer-based system (Chart 5 for Windows, AD Instruments, Shanghai, China) equipped with an analogue-to-digital converter (ML880 PowerLab 16/30, AD Instruments). The heel contact interval (HCI) was also measured by a foot switch sensor (Inline Foot Contact Sensor, Noraxon) from the right heel. The foot switch signal was collected with a sampling frequency of 1.5 kHz using a personal computer-based system (MyoResearch XP, Noraxon). The ECG and foot switch signals were reported by separate computers; therefore, we started maintaining records at the same time. In addition, subject's V[O.sub.2] was measured breath by...

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