Blood Pressure Estimation Using Photoplethysmography Only: Comparison between Different Machine Learning Approaches

Table 1

The number of segments for each BP categorical groups, separately for each case.

Case	Normotensive	Hypertensive	Hypotensive	Bad quality signals	Without reference BPs	Total
Case 1	581	—	64	419	376	1440
Case 2	12	—	14	166	—	192
Case 3	1099	—	50	1400	1051	3600
Case 4	496	—	—	649	295	1440
Case 5	50	32	—	352	1726	2160
Case 6	357	56	69	158	80	720
Case 7	128	—	56	289	247	720
Case 8	248	—	—	296	152	696
Case 9	465	—	—	178	77	720
Case 10	44	1	—	195	—	240
Case 11	395	51	71	203	—	720
Case 12	312	—	392	468	268	1440
Case 13	324	—	8	223	165	720
Case 14	—	—	61	95	—	156
Case 15	—	—	12	158	—	170
Case 16	—	—	46	86	28	160
Case 17	65	—	4	70	27	166
Case 18	81	—	—	81	—	162
Case 19	40	15	—	84	20	159
Case 20	286	3	11	256	164	720
Case 21	101	0	59	119	81	360
Case 22	56	52	11	167	74	360
Case 23	22	76	—	226	—	324
Case 24	20	—	—	160	—	180
Case 25	101	57	19	468	75	720
Case 26	152	21	7	367	173	720
Case 27	98	—	—	388	101	720
Case 28	231	—	—	403	79	720
Case 29	211	—	27	480	—	720
Case 30	48	—	—	84	—	132
Case 31	315	72	34	798	221	1440
Case 32	144	200	—	286	90	720
Total	6482	636	1015	9772	5570	23617