This paper presents a framework for hand gesture recognition based on the information fusion from a body-attached multisensor technology comprising a smart glove, a smart band, and an inertial measurement unit (IMU). The smart glove is integrated with nanocomposite filament strain sensors developed from carbon nanotubes (CNT) dispersed in thermoplastic polyurethane (TPU) and extruded as filaments using a micro-compounder. The smart band is integrated with nanocomposite pressure sensors developed from CNTs dispersed in a silicone polymer, polydimethylsiloxane (PDMS), and deposited as a thin sheet that is cut as circular disks and coupled with underlying interdigital electrodes. The (IMU) comprising of a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer and is fabricated along with the sensor interface and single processing unit. The paper elaborates on the development of the nanocomposite sensors and the performance of these three sensor technologies by studying ten American Sign Language (ASL) gestures representing numbers 1 to 10 without the involvement of a sophisticated machine learning algorithm for gesture classification. The outcome of this investigation provides valuable insights into the performance of the individual sensor technology in comparison to their counterparts and sets guidelines for further development of such body-attached systems in terms of the type and selection of sensor technology and the required number of sensors. The hardware architecture of the developed framework can be directly implemented as a potential tool for human–machine interface-related activities.