Human limb movement intent recognition fundamentally provides the control mechanism for assistive devices such as exoskeleton and limb prosthesis. While different biopotential signals have been utilized for limb movement intent decoding, they seldom could account for spatial information associated with changes in muscle shape that could also be used to characterize the limb motor intent. Therefore, this study developed a novel nano gold stretchable-flexible sensor that captures spatial information associated with the muscle shape change signal (MSCS) during different muscle activation patterns. The novel sensor consists of 2-channels to acquire MSCS at a sampling rate of 125 Hz, corresponding to multiple classes of upper limb movements acquired across six able-bodied subjects. By utilizing the linear discriminant analysis algorithm on the acquired data with a single extracted feature, an overall average motion decoding accuracy of 90.9% was achieved. In addition, the waveform analysis results show that the novel sensor's recordings were less affected by external interferences, thus yielding high quality signals. This study is the first to utilize nano gold stretchable-flexible material for sensor fabrication in pattern recognition of upper limb movement intent, which may facilitate the development of effective assistive devices.