The number of people with physical disabilities is increasing year by year, and the trend of population aging is more and more serious. In order to improve the quality of the life, a control system of accessible home environment for the patients with serious disabilities was developed to control the home electrical devices with the voice of the patients. The control system includes a central control platform, a speech recognition module, a terminal operation module, etc. The system combines the speech recognition control technology and wireless information transmission technology with the embedded mobile computing technology, and interconnects the lamp, electronic locks, alarms, TV and other electrical devices in the home environment as a whole system through a wireless network node. The experimental results showed that speech recognition success rate was more than 84% in the home environment.
Computers ; Disabled Persons ; Humans ; Speech Recognition Software ; Wireless Technology

Objective:To investigate protective effect of Pinus massoniana needle extract (PMNE) against oxidative stress in human dermal papilla cells (HDPC) , and to explore its mechanisms. Methods:As research objects, some cultured HDPC were treated with H 2O 2 at different concentrations of 0 (control group) , 0.1, 0.2, 0.4, 0.8 and 1.0 mmol/L, in order to establish the optimal condition for in vitro oxidative stress in HDPC; some other HDPC were transfected with nuclear factor-erythroid 2-related factor 2 (Nrf2) specific small interfering RNAs (siRNA1, siRNA2, siRNA3) or a Nrf2-overexpressing plasmid (pCMV6-XL5-Nrf2) , the HDPC transfected with a scrambled-siRNA and an empty plasmid pCMV6-XL5 served as the control siRNA group and control plasmid group respectively, and HDPC subjected to conventional culture served as the blank group; after the above treatment, real-time fluorescence-based quantitative PCR and Western blot analysis were performed to determine Nrf2 mRNA and protein expression, respectively; cell viability and apoptosis were detected in the above transfected cells after the treatment with H 2O 2 at an optimal concentration. In the subsequent experiment, some HDPC were divided into several groups: control group subjected to conventional culture, dihydrotestosterone group treated with 0.03 μg/ml dihydrotestosterone, proanthocyanidin group treated with 0.03 μg/ml dihydrotestosterone and 6.00 μg/ml proanthocyanidin B2, PMNE groups treated with 0.03 μg/ml dihydrotestosterone and PMNE at different concentrations of 1, 5, 25 and 100 μg/ml; after the above treatment, cell viability and apoptosis were detected, relative fluorescence intensity of intracellular reactive oxygen species (ROS) , malondialdehyde (MDA) content, mRNA and protein expression of Nrf2, quinone oxidoreductase 1 (NQO1) , heme oxygenase 1 (HO-1) , Kelch-like ECH-related protein 1 (Keap1) , transforming growth factor (TGF) -β1, Sma- and Mad-related protein 2/3 (Smad2/3) , phosphorylated Smad2/3 (p-Smad2/3) were determined in HDPC. One-way analysis of variance was used for comparisons among multiple groups, and least significant difference- t test for multiple comparisons. Results:The viability of HDPC ranged from 75% to 85% after the treatment with 0.4 mmol/L H 2O 2, which was selected as the optimal condition for in vitro oxidative stress in HDPC. Compared with the blank group and control siRNA group, the Nrf2-siRNA1, Nrf2-siRNA2, Nrf2-siRNA3 groups showed significantly decreased Nrf2 mRNA and protein expression (all P < 0.05) , but significantly increased apoptosis rate (Nrf2-siRNA1, Nrf2-siRNA2, Nrf2-siRNA3 groups, blank group and control group: 12.50% ± 0.05%, 26.07% ± 0.05%, 58.44% ± 1.03%, 10.38% ± 0.64%, 13.05% ± 0.12%, respectively; all P < 0.05) . Nrf2 protein expression was the lowest in the Nrf2-siRNA2 group, so Nrf2-siRNA2 was selected as the optimal interfering fragment for subsequent experiments. Compared with the blank group and control plasmid group, the Nrf2 overexpression group showed significantly increased Nrf2 mRNA and protein expression (both P < 0.05) , but a significantly decreased apoptosis rate (all P < 0.05) . After the treatment with 0.4 mmol/L H 2O 2, the Nrf2 overexpression group showed a significantly decreased apoptosis rate, but significantly increased cell viability compared with the empty vector group ( t = 3.66, 40.40, respectively, both P < 0.001) ; the Nrf2-siRNA2 group showed a significantly increased apoptosis rate, but significantly decreased cell viability compared with the control group ( t = 13.13, 67.37, respectively, both P < 0.001) . In the PMNE treatment experiment, the proanthocyanidin group and PMNE groups showed significantly increased cell viability, but significantly decreased apoptosis rates compared with the dihydrotestosterone group (all P < 0.01) ; proanthocyanidin and PMNE at different concentrations could significantly inhibit dihydrotestosterone-induced overexpression of ROS and MDA in HDPC (all P < 0.01) ; the protein expression of Nrf2, NQO1 and HO-1 was significantly higher in the proanthocyanidin group, 5-, 25- and 100-μg/ml PMNE groups than in the dihydrotestosterone group (all P < 0.05) , while the protein expression of Keap1 and TGF-β1, and the Smad2/3 phosphorylation level were significantly lower in the proanthocyanidin group, 25- and 100-μg/ml PMNE groups than in the dihydrotestosterone group (all P < 0.05) . Conclusion:Nrf2 plays an important role in protecting against oxidative damage in HDPC, and PMNE may exert marked protective effect on HDPC by activating the Nrf2-antioxidant responsive element signaling pathway.

Objective:To design a new type of intelligent power-assisted hip disarticulation prosthesis and to use experiments to verify its kinematic performance.Methods:The main body of the prosthesis was designed using a double parallel four-link configuration based on a remote motion center mechanism. A series elastic actuator was used to provide external power for the prosthesis, and an antagonistic torsion spring structure was used to achieve bidirectional energy storage assistance in hip flexion and extension. A control system based on impedance control was established. By setting up an auxiliary force field to compensate for the difference between the actual angle of the prosthesis and the target angle, the prosthesis assist function was realized. Finally, the traditional hip disarticulation prosthesis was used as a comparison to test the overall performance of the new intelligent power-assisted hip disarticulation prosthesis worn by normal people.Results:For the new smart-assisted hip-disarticulation prosthesis, the goodness-of-fit of its hip joint angle curve to that of a normal person was 86%, which was 14% higher than that of the traditional hip-disarticulation prosthesis (72%). The goodness-of-fit of the healthy-side angle of the new smart-assisted hip disarticulation prosthesis to the normal human was 94%, which was the same as that of the traditional hip disarticulation prosthesis.Conclusions:A new type of intelligent power-assisted hip disarticulation prosthesis is designed to realize the function of prosthesis-assisted movement.

Objective:To assess the diagnostic efficacy of upper gastrointestinal endoscopic image assisted diagnosis system (ENDOANGEL-LD) based on artificial intelligence (AI) for detecting gastric lesions and neoplastic lesions under white light endoscopy.Methods:The diagnostic efficacy of ENDOANGEL-LD was tested using image testing dataset and video testing dataset, respectively. The image testing dataset included 300 images of gastric neoplastic lesions, 505 images of non-neoplastic lesions and 990 images of normal stomach of 191 patients in Renmin Hospital of Wuhan University from June 2019 to September 2019. Video testing dataset was from 83 videos (38 gastric neoplastic lesions and 45 non-neoplastic lesions) of 78 patients in Renmin Hospital of Wuhan University from November 2020 to April 2021. The accuracy, the sensitivity and the specificity of ENDOANGEL-LD for image testing dataset were calculated. The accuracy, the sensitivity and the specificity of ENDOANGEL-LD in video testing dataset for gastric neoplastic lesions were compared with those of four senior endoscopists.Results:In the image testing dataset, the accuracy, the sensitivity, the specificity of ENDOANGEL-LD for gastric lesions were 93.9% (1 685/1 795), 98.0% (789/805) and 90.5% (896/990) respectively; while the accuracy, the sensitivity and the specificity of ENDOANGEL-LD for gastric neoplastic lesions were 88.7% (714/805), 91.0% (273/300) and 87.3% (441/505) respectively. In the video testing dataset, the sensitivity [100.0% (38/38) VS 85.5% (130/152), χ2=6.220, P=0.013] of ENDOANGEL-LD was higher than that of four senior endoscopists. The accuracy [81.9% (68/83) VS 72.0% (239/332), χ2=3.408, P=0.065] and the specificity [ 66.7% (30/45) VS 60.6% (109/180), χ2=0.569, P=0.451] of ENDOANGEL-LD were comparable with those of four senior endoscopists. Conclusion:The ENDOANGEL-LD can accurately detect gastric lesions and further diagnose neoplastic lesions to help endoscopists in clinical work.

Objective:To construct a real-time artificial intelligence (AI)-assisted endoscepic diagnosis system based on YOLO v3 algorithm, and to evaluate its ability of detecting focal gastric lesions in gastroscopy.Methods:A total of 5 488 white light gastroscopic images (2 733 images with gastric focal lesions and 2 755 images without gastric focal lesions) from June to November 2019 and videos of 92 cases (288 168 clear stomach frames) from May to June 2020 at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University were retrospectively collected for AI System test. A total of 3 997 prospective consecutive patients undergoing gastroscopy at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University from July 6, 2020 to November 27, 2020 and May 6, 2021 to August 2, 2021 were enrolled to assess the clinical applicability of AI System. When AI System recognized an abnormal lesion, it marked the lesion with a blue box as a warning. The ability to identify focal gastric lesions and the frequency and causes of false positives and false negatives of AI System were statistically analyzed.Results:In the image test set, the accuracy, the sensitivity, the specificity, the positive predictive value and the negative predictive value of AI System were 92.3% (5 064/5 488), 95.0% (2 597/2 733), 89.5% (2 467/ 2 755), 90.0% (2 597/2 885) and 94.8% (2 467/2 603), respectively. In the video test set, the accuracy, the sensitivity, the specificity, the positive predictive value and the negative predictive value of AI System were 95.4% (274 792/288 168), 95.2% (109 727/115 287), 95.5% (165 065/172 881), 93.4% (109 727/117 543) and 96.7% (165 065/170 625), respectively. In clinical application, the detection rate of local gastric lesions by AI System was 93.0% (6 830/7 344). A total of 514 focal gastric lesions were missed by AI System. The main reasons were punctate erosions (48.8%, 251/514), diminutive xanthomas (22.8%, 117/514) and diminutive polyps (21.4%, 110/514). The mean number of false positives per gastroscopy was 2 (1, 4), most of which were due to normal mucosa folds (50.2%, 5 635/11 225), bubbles and mucus (35.0%, 3 928/11 225), and liquid deposited in the fundus (9.1%, 1 021/11 225).Conclusion:The application of AI System can increase the detection rate of focal gastric lesions.

Objective Aiming at the problems of lacking initiative in upper limb rehabilitation training equipment, single training mode, and low active participation of patients, an upper limb continuous motion estimation algorithm model based on multi-modal information fusion was proposed, so to realize accurate estimation of elbow joint torque. Methods Firstly, the surface electromyography (sEMG) signal and posture signal of participants were collected at four angular velocities, and the time domain characteristics of the signal were extracted. The principal component analysis was adopted to multi-feature fusion. The back propagation neural network (BPNN) was optimized through the additional momentum and the adaptive learning rate method. The particle swarm optimization (PSO) algorithm was used to optimize the neural network and a continuous motion estimation model based on PSO-BPNN was constructed. Finally, the joint torque calculated by the second type of Lagrangian equation was used as the accurate value to train the model. The performance of the model was compared with the traditional BP neural network model. Results The root mean square error (RMSE) of the traditional BP neural network model was 558.9 N·m, and the R2 coefficient was 77.19%, Whereas the RMSE and the R2 coefficient of the optimized model were 113.6 mN·m and 99.12%, respectively.Thereby, the accuracy of torque estimation was improved apparently. Conclusions The method for continuous motion estimation of the elbow joint proposed in this study can estimate the motion intention accurately, and provide a practical scheme for the active control of upper exoskeleton rehabilitation robot.