Health Timer vs HearTomo

This application is to manage your daily exercises. Let's exercise with the cute tiger every day! ◎ Function ◎ - My menu You can manage your daily exercises by the list. - Count down timer You can register a "set" and "time" for each exercise, will inform exercise is finished by an alarm. - Stamp album You can view the history of exercises in a calendar. - Reminder Will inform the time of exercise start by an alarm. (For example : 6 PM) - Search and save the way of exercise When you want to know the correct way of exercise, can search on the Internet, and save the page's URL. - Bonus If you done your daily exercises, get a coin. It can buy wallpapers.

HearTomo is an app that works with Apple Health to perform 1/f fluctuation slope, Lorenz plot, and emotion analysis from ECG data from Apple Watch. 1/f Fluctuation Slope Value The heartbeat interval RRI data is converted to power spectral density PSD and the 1/f fluctuation slope value is calculated. You can see the value change over time in a graph: day, week, month, 6 months, and 1 year. Lorenz Plot One of the time domain indicators of autonomic nerve activity, RRI(n) is the interval between the nth heartbeat and the heartbeat before it. The value of RRI(n) is plotted on the x-axis and the value of RRI(n+1) on the y-axis. Order-made Emotion Analysis The accumulated data of the user is learned and updated daily to estimate emotions that suit the individual. The activity status of the sympathetic and parasympathetic nerves is classified into four states: "Both nerves are high", "Only sympathetic nerves are high", "Only parasympathetic nerves are high", and "Both nerves are low". Emotions are estimated as "inner voice". HearTomo's basic technology HearTomo development is based on the heart rate data analysis system patent 6430729 in collaboration with ZMP and Mr. Osaka Motohisa (graduate of the Department of Mathematics, Faculty of Science, University of Tokyo and the Department of Medicine, Faculty of Medicine, Nippon Medical School, currently Professor Emeritus, Nippon Veterinary and Life Science University). Mr. Osaka Motohisa conducted heart rate fluctuation analysis using his own calculation formula and an algorithm for spectral analysis of heart rate variability developed by Professor Ronald Berger from Johns Hopkins University Hospital. To improve the accuracy of the analysis, let's capture a clean heart rate waveform. Fix your arm on a table or your knee, and keep your fingers still for 30 seconds. After scrolling down to see the measurement results and tapping 'Done,' perform another 30-second measurement. A total of 4 repetitions, requiring 2 minutes of data, is necessary, and compared to other apps' 30-second measurements, HearTomo offers 4 times higher accuracy. Try to perform 4 consecutive measurements without leaving too much time between them. Website: https://heartomo.com/?lang=en Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/