RESUMO
Functional electrical stimulation (FES) devices are widely employed for clinical treatment, rehabilitation, and sports training. However, existing FES devices are inadequate in terms of wearability and cannot recognize a user's intention to move or muscle fatigue. These issues impede the user's ability to incorporate FES devices into their daily life. In response to these issues, this paper introduces a novel wearable FES system based on customized textile electrodes. The system is driven by surface electromyography (sEMG) movement intention. A parallel structured deep learning model based on a wearable FES device is used, which enables the identification of both the type of motion and muscle fatigue status without being affected by electrical stimulation. Five subjects took part in an experiment to test the proposed system, and the results showed that our method achieved a high level of accuracy for lower limb motion recognition and muscle fatigue status detection. The preliminary results presented here prove the effectiveness of the novel wearable FES system in terms of recognizing lower limb motions and muscle fatigue status.
Assuntos
Fadiga Muscular , Dispositivos Eletrônicos Vestíveis , Humanos , Eletromiografia , Estimulação Elétrica , Extremidade InferiorRESUMO
8-Aminoquinoline (AQ) has proven to be a highly effective bidentate directing group for palladium-catalyzed C-H functionalization reactions. However, enantiocontrol of AQ-directed C(sp3)-H functionalization reactions has been challenging. Herein, a new protocol is presented for the Pd-catalyzed enantioselective arylation of unactivated ß C(sp3)-H bonds of alkyl carboxamides with aryl iodides using a C5-iodinated 8-aminoquinolines (IQ) auxiliary in conjugation with a BINOL ligand. Additionally, a C5-aryl substituted 8-aminoquinoline auxiliary can facilitate enantioselective alkenylation and alkynylation of benzylic C(sp3)-H bonds of 3-arylpropanamides with the corresponding bromide reagents under similar conditions.