Applications of Artificial intelligence (AI) and soft computing techniques are rapidly growing biomedical research fields. This review article summarizes the most recent advances in detecting and classifying human gait parameters developed over the last forty years. The study explains various initiatives that can help increase the role of soft computing techniques in the health sector in diagnosing and treating diseases much faster. The proposed overview describes the conventional to recent advancements in the subject, including detecting neurodegenerative diseases by applying multimodal medical picture fusion, transfer learning, and deep learning. The techniques in the current paper have been validated with the Gait in Neurodegenerative Disease Database for raw sensor force data collected for left and right foot gait signals for neurodegenerative disease and healthy subjects, which are available online, i.e., PhysioNet.