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Individuals often pinch with preferred pinch techniques based on their experience and familiarity. However, researchers believe that pinch force exertions are not comparable across different pinch techniques. Hence, it is possible to pinch objects with incompatible pinch techniques during manual handling. This increases risks of developing musculoskeletal disorders. The preceding problem substantiates the need for a comprehensive understanding of definitions, categorisations and capacities of different pinch techniques. Nevertheless, the knowledge on pinch techniques appears to be highly dispersed and not compiled to a level systematic enough for further research. Thus, this review aims to develop a consolidated theoretical groundwork on pinch techniques. It presents an anthology of terminologies, previous findings and concepts underpinning different pinch techniques. While much research is still required, it is believed that an improved understanding on pinch techniques is now within sight, due to, in part, a structured review of their definitions, classifications and capacities. [ABSTRACT FROM PUBLISHER]

Although studies show that torque and sensation are important factors to consider in grip force, there appears to be few frameworks that focus on their roles in pinch force. This study proposes a framework that potentially explains the roles of torque and sensation in pinch force. A review was done on these factors followed by a literature synthesis which categorised them into sub-factors. The sub-factors were combined to output a framework that explains the mechanisms of their interactions. This framework enriches the knowledge on pinch force levels for reduced injury risks by identifying preliminary factors that may influence pinch force. It can potentially be used to improve the effectiveness of manufacturing tasks. Although further research on it is required, it still provides researchers with more factors to consider for studies on occupational risks and injuries. With this framework, researchers can potentially improve predictions on functional outcomes in precision manufacturing tasks. [ABSTRACT FROM PUBLISHER]