By correlating user grip information with micro-mobility events, electronic devices can provide support for a broad range of interactions and contextually-dependent techniques. Such correlation allows electronic devices to better identify device usage contexts, and in turn provide a more responsive and helpful user experience, especially in the context of reading and task performance. To allow for accurate and efficient device usage context identification, a model may be used to make device usage context determinations based on the correlated gesture and micro-mobility data. Once a context, device usage context, or gesture is identified, an action can be taken on one or more electronic devices.