# An AI-Based Exercise Prescription Recommendation System
## 4 Discussion  
In this study, we constructed an exercise prescription system by real-world exercise data. However, the total amount of real-world data still remains lots of insufficient. Data oversampling and synthesis is applied to overcome the problem in this paper. Apart from this, the system has not been online to Joisports platform for further testing yet. It will be a part of our future work. Such study is needed to further improve the structure, learning function, design, and also examine relations between exercise prescription and practical benefits. Eating preferences, drug history and other daily habits are not considered in this study. These variables will be added to our exercise prescription system for more precise recommendations. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**1m-SEM (_n = 773_)**} \\ \hline \multirow{5}{*}{(A)} & & **G1 (_n = 211_)** & **G2 (_n = 163_)** & **G3 (_n = 279_)** & **G4 (_n = 120_)** \\ \cline{2-6}  & Effective exercise time & 3202 & 3249 & 3152 & 3178 \\  & Average exercise HR & 126 & 124 & 128 & 126 \\  & Type of exercise & 1, 4 & 1, 9 & 1, 4 & 1, 4 \\  & Mets-min & 7324 & 8163 & 5922 & 9395 \\  & Exercise frequency & 3.31 & 3.36 & 3.13 & 3.61 \\ \hline \hline \multirow{5}{*}{(B)} & & **2m-SEM (_n = 410_)** & & & \\ \cline{2-6}  & & **G1 (_n = 158_)** & **G2 (_n = 85_)** & **G3 (_n = 68_)** & **G4 (_n = 99_)** \\ \cline{2-6}  & Effective exercise time & 3109 & 3260 & 3351 & 3269 \\  & Average exercise HR & 127 & 124 & 121 & 128 \\  & Type of exercise & 1, 4 & 1, 4 & 1, 9 & 1, 9 \\  & Mets-min & 7001 & 11,431 & 9245 & 8377 \\  & Exercise frequency & 3.51 & 4.48 & 4.16 & 3.26 \\ \hline \hline \multirow{5}{*}{(C)} & & **3m-SEM (_n = 269_)** & & & \\ \cline{2-6}  & & **G1 (_n = 60_)** & **G2 (_n = 103_)** & **G3 (_n = 58_)** & **G4 (_n = 48_)** \\ \cline{2-6}  & Effective exercise time & 3344 & 3373 & 3198 & 3206 \\  & Average exercise HR & 124 & 125 & 127 & 124 \\  & Type of exercise & 1, 9 & 1, 4 & 1, 4 & 1, 4 \\  & Mets-min & 8918 & 10,900 & 8511 & 7211 \\  & Exercise frequency & 3.87 & 4.08 & 4.14 & 3.55 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: (**A**). The recommended exercise indices of 1m-SEM in each group; (**B**). The recommended exercise indices of 2m-SEM in each group; (**C**). The recommended exercise indices of 3m-SEM in each group. Unit of effective exercise time: Seconds/each single exercise. Unit of average exercise HR: BPM/each single exercise. Type of exercise: 1′ refers to running, ‘4′ refers to hiding, ‘9′ refers to indoor exercise. Unit of Mets-min: (METs \(\times\) minute)/per month. Unit of exercise frequency: times/each week. G1: group 1. G2: group 2. G3: group 3. G4: group 4. The data with rest HR dropped more than 4 BPM after one-month, two-month and three-month exercise are the criterion to extract training data in the experiment. Recently, Joiisports developed a human body dash board able to collect five-dimension body information [26]. The user interface of the five-dimension human body dash board is illustrated in Figure 3. Those five dimensions including stamina, sleep, stress, vitals and shape. Stamina including rest HR, HR recovery rate and VO2 max. Rest HR and HR recovery rate are two of the indices to evaluate the ability of cardiac function. VO2 max refers to the ability of body oxygen delivery and usage efficiency. Sleep including sleep quality and blood oxygen saturation. Sleep quality is evaluated by different sleep stages. Those sleep stages including awake, rapid eye movement (REM) sleep and non-REM sleep. Besides, both light sleep and deep sleep are occurred in non-REM sleep. Stress including daily stress, awaken stress and heart rate variability (HRV). Standard deviation of normal to normal intervals (SDNN) calculated from electrocardiogram or photoplethysmogram data is one of the indices used to evaluate HRV [27]. Usually, high SDNN value refers to better cardiac ability. Reasonably, cardiac beating with high variations is confidential to adapt different external situation.