Biometrics is a branch of science that applies statistical methods to recognize the human identity based on the physiological and behavioural attributes of the individual, such as fingerprints, face and voice. However, the rise of IoT and wearable solutions make it possible to extend the existing system with new channels. One of the most promising examples is biosignals (ECG, BIA, EEG, etc.).
The task is to verify if the individual is the person he/she claims to be. Alternately, it may be required to establish the identity of an unknown individual by comparison against a biometric database.
We have developed hardware for biosignal acquisition and algorithms for data processing and pattern recognition, wrapped with high-level API for easy integration with customer environment.
Signal measurements are made using the embedded electronics with a minimized analog front end. Data processing and classification are implemented to run in real-time on desktop or mobile platforms.The biometric system can be integrated in a cloud to improve the system performance over time using on-line learning. The core algorithms are based on mean filters, FIR filters, deep neural networks, wavelet transform, etc.
PCA
K-means
Decision trees
Linear models
PageRank
Digital filters
DTW
Deep learning
Probabilistic graphical models
CART
ensembles
unsupervised sound segmentation
recurrent models
bayesian approach
probabilistic programming
hmm
alexnet
vgg
vae
PCA
TF-IDF
LDA
SVM
Naive bayes
word2vec
attention models
Hi, we are Sciforce - a company where the integration of various branches of science builds up a powerful force to create robust software solutions. Working at the intersection of Computer Science with other technical, natural and humanitarian sciences let us go beyond traditional IT services and become both technical and scientific forces to our customers.