(1) Background: One of the main cardinal signs of Parkinson’s disease (PD) is rigidity, whose assessment is important for monitoring the patient’s recovery. The wrist is one of the joints most affected by this symptom, which has a great impact on activities of daily living and consequently on quality of life. The assessment of rigidity is traditionally made by clinical scales, which have limitations due to their subjectivity and low intra- and inter-examiner reliability. (2) Objectives: To compile the main methods used to assess wrist rigidity in PD and to study their validity and reliability, a scope review was conducted. (3) Methods: PubMed, IEEE/IET Electronic Library, Web of Science, Scopus, Cochrane, Bireme, Google Scholar and Science Direct databases were used. (4) Results: Twenty-eight studies were included. The studies presented several methods for quantitative assessment of rigidity using instruments such as force and inertial sensors. (5) Conclusions: Such methods present good correlation with clinical scales and are useful for detecting and monitoring rigidity. However, the development of a standard quantitative method for assessing rigidity in clinical practice remains a challenge.

Remote therapy frameworks play the main role in home-based telerehabilitation. These remote therapies are exergames that help in the physical and cognitive rehabilitation of the patient. The objective of this review is to present the frameworks of home-based therapies using exergames and to identify the points that can be improved in the development of future systems. To carry out this research, the criteria of the PRISMA were adopted. Literature searches were conducted up to April 2021 in the Web of Sicence, Pubmed, Cochrane, Embase and Scopus databases. The search query was: (("game*" OR "exergame*") AND ("rehabilitation") AND ("remote" OR "telerehabilitation" OR "telemedicine")). We have selected a total of fourteen studies. We found five types of frameworks: Client-Server, Web-Based, Layers, Cloud Based and Multi users. We identified that it may be advantageous to mix the features of these frameworks to have a cheaper home-based system and prevent the patient from having to purchase more powerful computers. In addition, there are some challenges that need to be studied that will also help reduce costs for the patient: 1) Reduce the need for high processing of exergames on the patient's computer; 2) Prevent the patient from having to purchase expensive external devices for motion tracking.