Table 6.
Analysis of the processing algorithm, performance evaluation, and software for the studies of the wearable category.
| Study 1 | Algorithm | Performance Evaluation | Performance Value | Analysis Software |
|---|---|---|---|---|
| Aitkulov 2019 [57,58] | Frequency analysis | Graphical comparison | - | - |
| Balasubramaniyam 2019 [59] | - | - | - | MATLAB |
| Bricout 2019 [60] | Adaptive reconstruction | Correlation factor | 0.64–0.74 | - |
| Chu 2019 [61] | Peak detection | Bland-Altman analysis Correlation factor |
0.99 (correlation) | MATLAB |
| Elfaramawy 2019 [62] | Peak detection | - | - | MATLAB |
| Fajkus 2019 [63] | Peak detection | Relative error Bland-Altman analysis |
3.9% (RE) | Labview |
| Hurtado 2019 [64] | Zero-crossing detection | Relative error Bland-Altman analysis |
0.4 bpm (BA, mean of difference –MOD–) | - |
| Jayarathna 2019 [65] | Peak detection | - | - | - |
| Kano 2019 [66] | Peak detection | Correlation coefficient Bland-Altman analysis |
0.88 (correlation) 0.026 bpm (BA, MOD) |
- |
| Karacocuk 2019 [67] | Frequency analysis | Correlation | - | MATLAB Microprocessor |
| Massaroni 2019 [68] | Custom algorithm | Relative error Linear regression Bland-Altman analysis |
4.03% (RE) 0.91–0.97 (r2) −0.06 (BA, MOD) |
MATLAB |
| Massaroni 2019 [69] | Peak detection | Bland-Altman analysis | 0.05 bpm (BA, MOD) | - |
| Nguyen 2019 [70] | Frequency analysis | - | - | - |
| Presti 2019 [71] | Peak detection | Percentage error | <4.71% (PE) | MATLAB Labview |
| Presti 2019 [72] | Peak detection | - | - | - |
| Puranik 2019 [73] | - | - | - | - |
| Soomro 2019 [74] | - | - | - | - |
| Xiao 2019 [75] | - | Graphical comparison | - | - |
| Yuasa 2019 [76] | Peak detection | Accuracy | 61.3–65.6% | MATLAB |
| Zhang 2019 [77] | Frequency analysis | - | - | - |
| Dan 2018 [78] | Zero-crossing detection | Bland-Altman analysis | 0.01–0.02 bpm (BA, MOD) | - |
| Koyama 2018 [79] | Frequency analysis | Absolute error | 4 bpm | Python |
| Malik 2018 [80] | - | Graphical monitoring | - | Python |
| Martin 2018 [81] | Custom algorithm | Mean absolute error Mean relative error Bland-Altman analysis |
2.7 bpm (MAE) 30.9% (MRE) 2.4 bpm (BA, MOD) |
MATLAB |
| Pang 2018 [82] | - | Graphical monitoring | - | - |
1 Note: The analysis for studies published before 2018 [2,3,17,21,49,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162] is included in Appendix A (Table A4).