Parkinson’s disease is the second most common neurodegenerative disorder, affecting nearly 1 million people in the US and is predicted to keep increasing. Parkinson’s disease is difficult to diagnose due to the similarity with other diseases that share the parkinsonian symptoms, thus increasing the probabilities of misdiagnosis. Therefore, it is relevant to develop diagnostic tools that are quantitatively based and monitoring tools that will improve the patient’s quality of life. Computer-based assessment systems have shown to be successful in this field through diverse approaches that can be classified in two main categories: sensor-based and computer vision-based systems. In this article a comprehensive review is performed to analyze the different approaches taken; moreover, their challenges and future perspectives are discussed.