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Refereed/Peer-reviewed Objectives: The aim of this systematic review was to critically review and synthesise the findings from primary studies on pitching mechanics and performance of healthy adult baseball pitchers. Design: Systematic review with meta-analysis. Methods: Eight English- and Japanese-language databases were systematically searched from inception to 22nd July 2022. Results: In total, 29 descriptive biomechanical studies were included. Overall study quality was moderate. In subgroup analyses, professional pitchers showed significantly higher stride length, peak shoulder internal rotation velocity, peak shoulder proximal force and ball velocity compared to collegiate pitchers. Conversely, collegiate pitchers were found to have significantly higher peak pelvis rotation velocity. Conclusions: Available normative data suggested potentially heterogeneous pitching mechanics and performance between professional and collegiate pitchers. However, the findings in this review should be interpreted cautiously. Since statistical heterogeneity was significant within most data sets, more detailed subgroup analyses are required. Additionally, more high-quality studies utilising measurement systems with established reliability are required to obtain accurate data in baseball pitching mechanics and performance.

A large population of non-speaking, motor-impaired individuals must rely on computer-based communication aids. These aids, in essence, present the user 'with a list of letters, words, or phrases that may be selected to compose the desired utterance. The resulting utterance may then be passed to a speech synthesizer or document preparation system. While m~my of these individuals desire to communicate in complete well-lormed sentences, the expenditure in effort and time is often prohibitive. The goal of this project is to increase the communication rate of physically disabled individuals by cutting down the number of items that must be selected in order to compose a well-formed utterance. We wish to do this while placing as little a burden on the user as possible.

We describe how movement is handled in a class of computational devices called active production networks (APNs). The APN model is a parallel, activation-based framework that has been applied to other aspects of natural language processing. The model is briefly defined, the notation and mechanism for movement is explained, and then several examples are given which illustrate how various conditions on movement can naturally be explained in terms of limitations of the APN device.