In　recent　years,　thanks　to　the　development　of　integrated　circuits,　clinical　medicine　has　witnessed　significant　advancements,　enabling　more　efficient　and　intelligent　treatment　approaches.　Particularly　in　the　field　of　neuromedical,　the　utilization　of　brain-machine　interfaces　(BMI)　has　revolutionized　the　treatment　of　neurological　diseases　such　as　amyotrophic　lateral　sclerosis,　cerebral　palsy,　stroke,　or　spinal　cord　injury.　The　BMI　acquires　neural　signals　via　recording　circuits　and　analyze　them　to　regulate　neural　stimulator　circuits　for　effective　neurological　treatment.　However,　traditional　BMI　designs,　which　are　often　isolated,　have　given　way　to　closed-loop　brain-machine　interfaces　(CL-BMI)　as　a　contemporary　development　trend.　CL-BMI　offers　increased　integration　and　accelerated　response　speed,　marking　a　significant　leap　forward　in　neuromedicine.　Nonetheless,　this　advancement　comes　with　its　challenges,　notably　the　stimulation　artifacts　(SA)　problem　inherent　to　the　structural　characteristics　of　CL-BMI,　which　poses　significant　challenges　on　the　neural　recording　front-ends　(NRFE)　site.　This　paper　aims　to　provide　a　comprehensive　overview　of　technologies　addressing　artifacts　in　the　NRFE　site　within　CL-BMI.　Topics　covered　will　include:　(1)　understanding　and　assessing　artifacts;　(2)　exploring　the　impact　of　artifacts　on　traditional　neural　recording　front-ends;　(3)　reviewing　recent　technological　advancements　aimed　at　addressing　artifact-related　issues;　(4)　summarizing　and　classifying　the　aforementioned　technologies,　along　with　an　analysis　of　future　trends.