The present invention is directed to methods for improving male fertility inter alia by increasing sperm count in a male subject. The methods of the invention comprise applying a positive electrical current below sensation level to at least one site of a scrotum of a subject in need thereof.

The present invention relates to a method for sperm quality determination, comprising: a) locating and tracking image data of a spermatozoon in a plurality of sequentially acquired volumetric groups of images of a sample that includes a plurality of freely swimming spermatozoa, wherein the sequential acquisition has been carried out by means of non-point scanning optical sectioning microscopy; b) extracting features from the image data, the extracted features being three-dimensional morphological and dynamics features of the head and flagellum of the spermatozoon; c) determining a quality score for the spermatozoon based on the extracted three-dimensional features, applying statistics, and conducting a comparison with benchmarks referring to spermatozoa morphology and dynamics; and d) providing the quality score.

The present invention also relates to a computer program and a system implementing the method of the invention.

Systems and techniques for automated sample analysis are described herein. In some embodiments, the system for automated sample analysis includes an imaging device for detecting optical signals encoded with information associated with a sample, a processor for generating a plurality of images of the sample based on the detected optical signals, and a machine learning model for determining an output indicative of one or more attributes of the sample based at least in part on the plurality of images of the sample. Data indicative of the one or more attributes of the sample may include: a presence of an inclusion in the sample, a size of an inclusion in the sample, a shape of an inclusion in the sample, a movement of an inclusion in the sample, and a number of an inclusion in the sample.

Systems and techniques for automated sperm analysis are described herein. In some embodiments, the system for automated sperm analysis includes an imaging device for detecting optical signals encoded with information associated with a sperm sample, a processor for generating a plurality of images of the sperm sample based on the detected optical signals, and a machine learning model for determining an output indicative of a health of the sperm sample based at least in part on the plurality of images of the sperm sample. Data indicative of the health of the sperm sample may include: concentration of sperm in the sperm sample, shape of sperm in the sperm sample, motility of sperm in the sperm sample, or any other suitable data indicative of the health of the sperm sample.

Aspects of the methods include volumetrically imaging testicular tissue by optical coherence tomography to identify a testicular tissue location that is likely to contain sperm; and m-mode scanning using optical coherence tomography the identified testicular location to determine whether sperm are at least likely to be present at the location. Methods may further include harvesting sperm from the location, e.g., for use in in vitro fertilization. Also provided are devices and systems for practicing the methods.

A system for determining differential temperature in body part includes a sensor device(s) with a base having first side and second side opposite to first side; and temperature-sensitive element(s) being provided on first side of base, wherein when sensor device(s) in use, first side is in contact with body part of user for predefined time period and temperature-sensitive element(s) senses temperatures of different regions of body part; camera(s) configured to capture image(s) of first side, wherein image(s) captured within given time period from time of removal of contact between first side and body part; processor(s) communicably coupled to camera(s), wherein processor(s) configured to: identify, in image(s), image segment(s) representing temperature-sensitive element(s); recognize pixel values of pixels image segment(s); determine temperatures of different regions of body part, based on pixel values of pixels in image segment(s), temperatures of different regions of body part form differential temperature profile of body part.