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Scientists develop new bacterial tool to improve, speed drug manufacturing

Biosensors developed by scientists at The University of Texas at Austin have the potential to improve the process of drug manufacturing using bacteria. ....

United States , University Of Texas At Austin , Nature Chemical , Drug Administration Approved , Drug Manufacturing ,

Live Bacteria Bang Out Solos on Graphene Drum

Dead bugs don’t, giving researchers a new way to assess antibiotic efficacy ....

Registration is now open for Biosensors for Medical Wearables Conference 2022

SAE Media Group is delighted to announce the 2nd Annual Biosensors for Medical Wearables Conference, taking place on the 24th and 25th of October 2022, in ....

United States , United Kingdom , City Of , Nikisha Galoria , Media Group Conferences , Media Group , Annual Biosensors , Medical Wearables Conference , Medical Wearables , Group Conferences , Medical Biosenors ,

"Non-invasive Human-machine Interface (HMI) Systems with Hybrid On-body" by Hao Zhou and Gursel Alici

In this work, we present a systematic review on non-invasive HMIs employing hybrid wearable sensor modalities for recognition of upper limb intentions. Different combinations of the sensors are investigated. As sEMG is dominant in the applications of externally powered prosthetic hands, it is involved in most hybrid sensor combinations. The combined use of sEMG and IMU is most studied in the literature as IMU is easy to be integrated. Though limited, the investigation on other hybrid modalities has been drawing more and more research attention and efforts, especially those with FMG and NIRS. For all the reported hybrid sensors, it is verified that this strategy can enrich the information of user intention and help the pattern recognition and/or intensity regulation of robotic hand/arm prosthesis. Though it is the trend, the development of these hybrid-sensor-based HMIs are still at the preliminary stage. More dedicated sensor fusion models and system architectures as well as new hybrid ....

Adaptive Learning , Human Machine Interface , Hybrid Modalities , Multi Modal , Obot Sensing Systems , Emg Fmg , Emg Mmg , Emg Nirs , Emg Smg , Sensor Fusion , Sensor Systems , Upper Limb Prosthesis ,