The dataset and source codes for the paper “Remote laser-speckle sensing of heart sounds for health assessment and biometric identification.”
The paper describes a contactless, machine-learning assisted method for heart-sound identification and quantification based on the remote measurement of the reflected laser speckle from the human neck skin surface. 
The *.m source code files are named according to the figure in the manuscript they refer to. 
The *.mat files contain the following data:
The dataset.mat file contains the heart beat sound recordings with our remote detection method. It contains a single matlab variable dataset, which is an array of 10x9x44100 double where the first dimension is the person ID, the second dimension runs over 9 different 30 sec recordings per person and the last dimension runs over signal samples at 1.5KSamples/sec. This data was used for training of our algorithm.

The testset.mat file contains recordings for the same people at the next day according to the first dataset. It contains a matlab variable test_set ,which is 10x9x44100 double. The first index is the person ID and is consistent with the The dataset.mat file. The second dimension is the same as in the dataset.mat file. 

The frames.mat file contains an example of the raw data recording of the speckle movement due to the heart beat perturbing the skin surface on the person’s neck. The file contains a frames matlab variable of the size 200x208x4000 double. The first two dimensions are the speckle images and the last dimension is signal samples over time.

The tsne_emb.mat file contains the TSNE embeddings of the processed signals shown in Fig 3. 

The f04_fig4a_sthethoscope.m file uses the hsct11 dataset (2013 18th International Conference on Digital Signal Processing (DSP), (IEEE, 2013), pp. 1–5) which can be downloaded at http://www.diit.unict.it/hsct11/
The stethoscope_rec.mat contains an example stethoscope recording taken from the hsct11 dataset (M2603PNR02D090521N830924.wav)