Intelligent recommendation method of an exercise program based on physical health data of college students

Figures & data

Table 1. Physical health diagnostic indicators.

Test items	First-level indicator	Secondary indicators
BMI	body shape	body type
lung capacity	Body Function	Heart and lung function
50 meters	physical fitness	Speed quality
Sitting forward bend	physical fitness	Flexibility
Standing long jump	physical fitness	Strength quality
pull up	physical fitness	Strength quality
1000 m/800 m	physical fitness	Endurance quality

Table 2. Student physical health evaluation system.

Evaluation method	Evaluation object
	Individual evaluation	Group evaluation
Rating evaluation	Single index score	Average score for boys Average score for girls
	Comprehensive Indicator Score	The composite indicator’s average score for boys The composite indicator’s average score for girls
Grade evaluation	Single index score	Average score for boys Average score for girls
	Comprehensive Indicator Score	The composite indicator’s average score for boys The composite indicator’s average score for girls

Figure 1. Architecture of exercise program recommendation system.

Figure 2. Classification process of physical health data based on improved K-means.

Figure 3. The decision-making process for generating motion plans.

Figure 4. The improved K-means algorithm flow chart.

Table 3. Examples of physical health data for boys.

BMI (kg/m^2)	lung capacity (ml)	Standing long jump (cm)	Sitting forward bend (cm)	50 meters (s)	pull up (pcs)	1000 meters (s)
21.86	4824	258	23.12	7.01	14	240
20.95	5140	217	20.86	7.16	13	239
22.47	3682	234	24.58	6.86	12	226
23.03	3897	226	26.52	7.27	15	231
21.55	4025	241	22.79	6.96	11	223
19.89	3783	239	25.64	7.12	10	217
20.68	5002	222	21.10	6.94	12	230
21.14	4268	240	22.03	7.43	11	251

Table 4. Examples of physical health data for girls.

BMI (kg/m^2)	lung capacity (ml)	Standing long jump (cm)	Sitting forward bend (cm)	50 meters (s)	pull up (pcs)	1000 meters (s)
17.96	3354	164	15.13	7.70	27	198
21.23	2865	173	13.85	7.82	30	195
20.85	2933	159	16.67	7.91	31	204
24.42	3432	182	12.54	8.42	29	210
22.57	3587	197	11.73	8.61	35	201
19.86	3364	166	10.72	8.92	38	199
21.31	3476	174	9.98	9.31	40	212
22.35	3022	181	14.36	10.0	32	224

Table 5. Center point vector of boys’ physical health data.

No.	Center Point Vector
1	[17.43,3248,168,15.62,7.72,28,189]
2	[20.23,2946,172,14.73,7.81,31,192]
3	[19.84,2862,161,16.18,7.98,33,201]
4	[22.53,3269,174,13.75,8.34,30,213]
5	[24.59,3387,184,12.79,8.53,36,225]
6	[19.50,3155,175,13.65,9.34,39,195]

Table 6. Center point vector of girls’ physical health data.

No.	Center Point Vector
1	[17.88,3367,165,14.75,7.72,29,199]
2	[20.15,2956,172,13.68,7.38,31,196]
3	[21.64,2852,161,15.63,8.13,32,202]
4	[23.48,3361,179,12.87,8.58,28,211]
5	[23.92,3563,183,11.74,8.84,34,204]
6	[19.69,3489,178,10.81,8.90,37,191]

Figure 5. Classification results of physical health data based on K-means.

Figure 6. Classification results of physical health data based on fuzzy C-Means.

Figure 7. Classification results of physical health data based on BP neural network.

Figure 8. Classification results of physical health data based on improved K-means.