Functional connectivity is a critical concept in describing synergistic muscle synchronization for the execution of complex motor tasks. Muscle synchronization is typically derived from the decomposition of intermuscular coherence (IMC) at different frequency bands through electromyography (EMG) signal analysis with limited out-of-clinic applications. In this investigation, we introduce muscle network analysis to assess the coordination and functional connectivity of muscles based on mechanomyography (MMG), focused on a targeted group of muscles that are typically active in the conduction of activities of daily living using the upper limb. In this regard, functional muscle networks are evaluated in this paper for ten able-bodied participants and three amputees. MMG activity was acquired from a custom-made wearable MMG armband placed over four superficial muscles around the forearm (i.e., flexor carpi radialis (FCR), brachioradialis (BR), extensor digitorum communis (EDC), and flexor carpi ulnaris (FCU)) while participants performed four different hand gestures. The results of connectivity analysis at multiple frequency bands showed significant topographical differences across gestures for low (< 5Hz) and high (> 12 Hz) frequencies and observable differences between able-bodied and amputee subjects. These findings show evidence that MMG can be used for the analysis of functional muscle connectivity and mapping of synergistic synchronization of upper-limb muscles in complex upper-limb tasks. The new physiological modality further provides key insights into the neural circuitry of motor coordination and offers the concomitant outcomes of demonstrating the feasibility of MMG to map muscle coherence from a neurophysiological perspective as well as providing the mechanistic basis for its translation into human-robot interfaces.