Information on daily physical activity is essential for determining daily nutritional demands and devising physical conditioning programs. In order to obtain reliable information on daily physical activity, it is necessary to record the activity in some way. Up to now, however, such data have been collected using retrospective questionnaires and observation, and by measurement of heart rate over extensive periods. These methods are too cumbersome and expensive.
The purpose of the present study was to develop a new device for recording physical activity in the form of an actogram. A pedometer was used to record the physical activity, and a microswitch was set inside the pedometer to convert the pedometer count into an electric signal, since it is advantageous to process the data by computer. The pedometer count was recorded in the IC memory of a computer with a 32-kbyte. The memorized pedometer count was fed into the personal computer through an interface, and after processing it was displayed as an actogram representing the activity pattern and the amount of physical activity.
The new device developed in this study could serve as a practical tool for recording the quantity and time course of physical activity during daily life, since it is small (110mm×70 mm×30 mm) and light (170g), less expensive and also convenient to handle.

This study aimed at clarifying the effects of a lifestyle intervention using an activity monitor with game functions on daily physical activity. A 12-week randomized crossover study was conducted in 23 healthy volunteers (31 ± 11 yrs). The subjects were randomly assigned to Group A (a 6-week game intervention and then a 6-week normal intervention) and Group B (a 6-week normal intervention and then a 6-week game intervention). In the game intervention period (G), the subjects wore two different activity monitors, namely a normal activity monitor (Lifecorder EX) and an activity monitor with game functions (Yuuhokei). On the other hand, in the normal intervention period (N), the subjects wore only a normal activity monitor. Daily steps were significantly higher in the G than in the N (G: 10417 ± 2358 vs. N: 8744 ± 2180 steps/day, P < 0.001). Amount of physical activity (i.e., daily total METs · hour = Ex/day) at the intensity of 3 METs or more was significantly higher in the G than in the N (G: 3.1 ± 0.9 vs. N: 2.4 ± 0.8 Ex/day, P < 0.001). Our results indicate that the lifestyle intervention using an activity monitor with game functions would more effectively increase daily physical activity such as steps and physical activity amount, than a normal intervention using an activity monitor. These findings therefore have important implications for reaching more easily the goals (i.e., 23 Ex/week or 10,000 steps/day) and the use of an activity monitor with game functions in the field of exercise or physical activity instructions.

This study aimed to clarify the effects of a lifestyle intervention by the concurrent use of an activity monitor and Twitter on daily physical activity. Twenty-one healthy males and females (37 ± 13 yrs) were randomly assigned to Normal intervention group (N group, n = 10) or Twitter intervention group (T group, n = 11). In both groups, the intervention period was 6 weeks. Participants in N group wore an activity monitor (Lifecorder EX). Meanwhile, participants in T group were asked to tweet about their daily steps or physical activity in addition to wearing an activity monitor, and also an observer read through the tweet from each participant and commented about physical activity. There were no significant differences in daily physical activity (i.e., steps and amount of physical activity (PA)) at week 1 between both groups. In addition, no significant time-course changes in steps and amount of PA were observed in N group. In contrast, steps in T group were gradually increased from week 1 8,542 ± 3,158 steps/day to week 6 12,700 ± 3,935 steps/day (P < 0.01). Amount of PA in T group was also gradually increased from week 1 2.5 ± 1.2 METs·hour/day to week 6 4.6 ± 2.3 METs·hour/day (P < 0.01). Therefore, these findings indicate that the lifestyle intervention by the concurrent use of an activity monitor and Twitter could effectively induce an increase in daily physical activity compared with the intervention using only an activity monitor.