TY  - JOUR
AU  - Tsai, Vincent FS
AU  - Zhuang, Bin
AU  - Pong, Yuan-Hung
AU  - Hsieh, Ju-Ton
AU  - Chang, Hong-Chiang
PY  - 2020
DA  - 2020/11/19
TI  - Web- and Artificial Intelligence–Based Image Recognition For Sperm Motility Analysis: Verification Study
JO  - JMIR Med Inform
SP  - e20031
VL  - 8
IS  - 11
KW  - Male infertility
KW  - semen analysis
KW  - home sperm test
KW  - smartphone
KW  - artificial intelligence
KW  - cloud computing
KW  - telemedicine
AB  - Background: Human sperm quality fluctuates over time. Therefore, it is crucial for couples preparing for natural pregnancy to monitor sperm motility. Objective: This study verified the performance of an artificial intelligence–based image recognition and cloud computing sperm motility testing system (Bemaner, Createcare) composed of microscope and microfluidic modules and designed to adapt to different types of smartphones. Methods: Sperm videos were captured and uploaded to the cloud with an app. Analysis of sperm motility was performed by an artificial intelligence–based image recognition algorithm then results were displayed. According to the number of motile sperm in the vision field, 47 (deidentified) videos of sperm were scored using 6 grades (0-5) by a male-fertility expert with 10 years of experience. Pearson product-moment correlation was calculated between the grades and the results (concentration of total sperm, concentration of motile sperm, and motility percentage) computed by the system. Results: Good correlation was demonstrated between the grades and results computed by the system for concentration of total sperm (r=0.65, P<.001), concentration of motile sperm (r=0.84, P<.001), and motility percentage (r=0.90, P<.001). Conclusions: This smartphone-based sperm motility test (Bemaner) accurately measures motility-related parameters and could potentially be applied toward the following fields: male infertility detection, sperm quality test during preparation for pregnancy, and infertility treatment monitoring. With frequent at-home testing, more data can be collected to help make clinical decisions and to conduct epidemiological research. 
SN  - 2291-9694
UR  - http://medinform.jmir.org/2020/11/e20031/
UR  - https://doi.org/10.2196/20031
UR  - http://www.ncbi.nlm.nih.gov/pubmed/33211025
DO  - 10.2196/20031
ID  - info:doi/10.2196/20031
ER  -