Table A5.
Analysis of the processing algorithm, performance evaluation, and software for the studies of the environmental category published before 2018.
| Study | Algorithm | Performance Evaluation | Performance Value | Analysis Software |
|---|---|---|---|---|
| Azimi 2017 [183] | Peak detection Custom algorithm |
Linear regression | 0.968 and 1.0223 (slope) | - |
| Cho 2017 [184] | Custom algorithm | - | - | - |
| Leicht 2017 [185] | - | Graphical comparison | - | MATLAB |
| Li 2017 [186] | Frequency analysis | Graphical monitoring | - | MATLAB |
| Li 2017 [187] | Custom algorithm | Root mean square error | 1.12 bpm | OpenCV |
| Prathosh 2017 [10] | Custom algorithm | Correlation factor Bland-Altman analysis |
0.94 (correlation) 0.88 bpm (BA, MOD) |
- |
| Prochazka 2017 [188] | Neural Network | - | - | - |
| Tataraidze 2017 [7] | Peak detection Custom algorithm |
Accuracy | 97% | MATLAB |
| Wang 2017 [189] | Frequency analysis (Short-Time Fourier Transform) | Absolute error | 0.11–0.33 bpm | - |
| Heldt 2016 [5] | Threshold detection | Mean absolute error | 1.2 bpm | Acknowledge |
| Kukkapalli 2016 [190] | Peak detection | Accuracy | >95% | |
| Prochazka 2016 [191] | Custom algorithm | Relative error | 0.06–0.26% | - |
| Tveit 2016 [192] | Phase-based respiration detection Pixel-intensity detection |
Manual verification Relative error |
7.21–11.57% | - |
| Ushijima 2016 [6] | - | Graphical comparison | - | - |
| Erden 2015 [193] | Wavelet transform Empirical mode decomposition |
Accuracy | 93% | - |
| Huang 2015 [54] | Peak detection Threshold detection |
- | - | - |
| Liu 2015 [194] | Peak detection Threshold detection |
Relative error | 1.8–5.7% | - |
| Pereira 2015 [195] | Custom algorithm | Correlation factor Mean Absolute Error Bland-Altman analysis |
0.92 (correlation) 0.53 bpm (MAE) 0.025 bpm (BA, MOD) |
MATLAB |
| Ravichandran 2015 [196] | Zero-crossing detection Frequency analysis Linear predictive coding Least-squares harmonic analysis |
Absolute error | 2.16 bpm | - |
| Sasaki 2015 [197] | - | Relative error | 3% | - |
| Zakrzewski 2015 [198] | Linear/ non-Linear demodulation | Mean squared error | - | MATLAB |
| Arlotto 2014 [199] | - | Graphical comparison | - | - |
| Bernacchia 2014 [200] | Custom algorithm | Correlation factor Bland-Altman analysis |
0.96 (correlation) 0 bpm (BA, MOD) |
MATLAB |
| Bernal 2014 [51] | Peak detection Zero-crossing detection Custom algorithm |
Graphical comparison | - | - |
| Chen 2014 [201] | Peak detection | Absolute error Relative error |
1.65 bpm (AE) 9.9% (RE) |
Labview |
| Lee 2014 [52] | Frequency analysis | Correlation factor Root mean square error |
0.90–0.976 (correlation) 0.0038–0.076 bpm (RMSE) |
MATLAB |
| Luis 2014 [202] | Custom algorithm | - | - | MATLAB |
| Mukai 2014 [203] | Frequency analysis | - | - | - |
| Nukaya 2014 [204] | - | Scatterplot | - | - |
| Patwari 2014 [205] | Frequency analysis | Relative error | 1 bpm | - |
| Patwari 2014 [206] | Custom algorithm | Relative error | 0.1 to 0.4 bpm | - |
| Shao 2014 [48] | Custom algorithm | Correlation factor Bland-Altman analysis Root mean square error |
0.93 (correlation) 0.02 bpm (BA, MOD) 1.2 bpm (RMSE) |
MATLAB |
| Taheri 2014 [207] | Custom algorithm | Mean absolute error Accuracy |
0.93–1.77 bpm (MAE) 79–89% (Acc) |
- |
| Wang 2014 [53] | Threshold detection | Others (confusion matrix) | 94% | - |
| Bartula 2013 [208] | Custom algorithm | Correlation factor | 0.98 | - |
| Chen 2013 [209] | Frequency analysis | Linear regression Bland-Altman analysis |
0.999 (r2) | - |
| Dziuda 2013 [210] | Max detection | Relative error Bland-Altman analysis |
<8% (RE) 0 bpm (BA, MOD) |
Custom application |
| Klap 2013 [211] | Proprietary algorithms | Relative error | 4–8% (RE) | - |
| Lau 2013 [19] | Peak detection | Correlation factor Mean absolute error |
0.971 (correlation) 2 bpm (MAE) |
Labview |
| Nijsure 2013 [50] | Custom algorithm | Correlation factor | 0.814 | - |
| Sprager 2013 [212] | Wavelet transform | Relative error | 7.37 ± 7.20% | MATLAB |
| Vinci 2013 [213] | Frequency analysis | Graphical comparison | - | MATLAB |
| Yavari 2013 [214] | - | Graphical comparison | - | - |
| Aoki 2012 [215] | Custom algorithm | Correlation factor Bland-Altman plot |
0.98 (correlation) | Kinect SDK |
| Boccanfuso 2012 [216] | Sinusoidal curve-fitting function | Accuracy | - | OpenCV |
| Bruser 2012 [217] | - | - | - | - |
| Chen 2012 [218] | Frequency analysis | Mean absolute error | 2 bpm | Labview |
| Dziuda 2012 [9,236] | Max-min detection | Relative error | 12% | C# |
| Gu 2012 [219] | - | Graphical comparison | - | Labview |
| Lokavee 2012 [220] | - | Graphical comparison | - | Labview |
| Shimomura 2012 [221] | Frequency analysis | Relative error | 1.61% | - |
| Xia 2012 [222] | - | Correlation factor | 0.958–0.978 | - |
| Lai 2011 [223] | Multipeak detection | Correlation factor | 0.5–0.83 | MATLAB Labview |
| Otsu 2011 [224] | Custom algorithm | Absolute error | 0.19 bpm | - |
| Postolache 2011 [225] | Peak detection | - | - | Labview Android app |
| Zito 2011 [226] | - | Graphical comparison | - | - |
| Heise 2010 [227] | Zero-crossing detection | - | - | - |
| Min 2010 [228] | Envelop detection Zero-crossing detection |
Correlation factor Bland-Altman analysis |
0.93–0.98 (correlation) −0.002–0.006 bpm (BA, MOD) |
MATLAB |
| Mostov 2010 [229] | Custom algorithm | - | - | - |
| Nishiyama 2010 [230,231] | - | Graphical monitoring | - | - |
| Scalise 2010 [232] | Wavelet transform | Correlation factor Bland-Altman analysis |
0.98 (correlation) 13 ms (BAP, MOD) |
- |
| Silvious 2010 [233] | - | Graphical comparison | - | - |
| Tan 2010 [234] | Custom algorithm | Graphical comparison | - | Custom application |