Objective To research the relationship between decrease of serum surfactant protein D (SP-D) level reduced by pulmonary rehabilitation training and postoperative pulmonary complications (PPC). Methods From May 2015 through December 2015, 80 consecutive non-small cell lung cancer (NSCLC) patients with surgical treatment in West China Hospital, who were at least with a high risk factor, were randomly divided into two groups including a group R and a group C. There were 36 patients with 25 males and 11 females at age of 63.98±8.32 years in the group R and 44 patients with 32 males and 12 females at age of 64.58±6.71 years in the group C.The group R underwent an intensive preoperative pulmonary rehabilitation (PR) training for one week, and then with lobectomy. The group C underwent only lobectomy with conventional perioperative managements. Postoperative pulmonary complications, average days in hospital, other clinic data and the serum SP-D level in a series of time from the date of admission to discharge (5 time points) were analyzed. Results The incidence of PPC in the group R was 5.56%(2/36),which was lower than that in the group C (P=0.032). The descender of the serum SP-D level of the patients in the group R (30.75±5.57 ng/mlvs. 24.22±3.08 ng/ml) was more obvious than that in the group C (31.16±7.81 ng/mlvs. 30.29±5.80 ng/ml,P=0.012). The descender of the serum SP-D level of the patients with PPC was more obvious than that of patients without PPC (P=0.012). Conclusion The preoperative PR training could reduce the PPC of lung cancer surgery with high risk factors. The serum SP-D level could reflect the effect of preoperative pulmonary rehabilitation training.
This article presents the design of a motion control system for seated lower-limb rehabilitation training. The system is composed of lower limb exoskeleton, motor drive circuit, program of motion control, and so forth. The power of lower limbs joints is provided by six motors. The PCI-1240 motion control card is used as the core. This study achieved repetitive rotation training and gait trajectory training of lower limbs joints, of which the velocity, angle and time can be accurately controlled and adjusted. The experimental results showed that the motion control system can meet the requirement of repetitive rehabilitation training for patients with lower limb dysfunction. This article provides a new method to the research of motion control system in rehabilitation training, which can promote industrial automation technique to be used for health care, and conducive to the further study of the rehabilitation robot.
This research is to develop a weight-loss walking rehabilitation training system based on differential air pressure. The system adopted Proportion-Integral-Derivative (PID) algorithm to improve the precision of weight loss, taking MSP430F149 microprocessor of Texas Instruments as the core of pressure control system. The training software is designed based on Microsoft Visual C++ 6.0 of Microsoft. The system can provide comfortable training environment for patients with lower limb motor function impediment, and can collect electromyographic signals from patients, so as to further the scientific and normative management of the patient's information. Based on this training system, the initial bearing weight, bearing weight after maximum weight loss, and maximum weight loss percentage of 10 normal adults’ lower limbs were collected. It was found that the intraclass correlation coefficient (ICC) values were all greater than 0.6. The training system has a good reliability, which can provide scientific data for clinical weight-loss lower limb rehabilitation training.
Human motion recognition (HAR) is the technological base of intelligent medical treatment, sports training, video monitoring and many other fields, and it has been widely concerned by all walks of life. This paper summarized the progress and significance of HAR research, which includes two processes: action capture and action classification based on deep learning. Firstly, the paper introduced in detail three mainstream methods of action capture: video-based, depth camera-based and inertial sensor-based. The commonly used action data sets were also listed. Secondly, the realization of HAR based on deep learning was described in two aspects, including automatic feature extraction and multi-modal feature fusion. The realization of training monitoring and simulative training with HAR in orthopedic rehabilitation training was also introduced. Finally, it discussed precise motion capture and multi-modal feature fusion of HAR, as well as the key points and difficulties of HAR application in orthopedic rehabilitation training. This article summarized the above contents to quickly guide researchers to understand the current status of HAR research and its application in orthopedic rehabilitation training.
ObjectiveTo explore the clinical effect of the end-traction upper limb rehabilitation training system on patients with upper limb motor dysfunction after stroke.MethodsPatients with upper limb motor dysfunction who were admitted to the Department of Rehabilitation Medicine, the First Affiliated Hospital of Nanchang University from September to November 2019 were selected. According to the software, the patients were randomly divided into the experimental group and the control group. Both groups received conventional medical treatment, basic rehabilitation, and activities of daily living training. In addition, the control group received traditional occupational therapy, while the experimental group received end-traction upper limb rehabilitation training. The training time of both groups was 30 min/ (times ·d) and 5 days per week. Rehabilitation evaluation and recording were performed before and after the four-week treatment in both groups using the simplified upper extremity Fugl-Meyer assessment (FMA) and the modified Barthel index (MBI).ResultsA total of 36 patients were enrolled, with 18 in each group. All patients completed the experiment, and no special discomfort was observed. Before the treatment, there was no statistically significant difference in FMA and MBI between the experimental group [(13.22±3.13) and (49.66±6.81) points] and the control group [(14.78±1.70) and (51.67±6.65) points] (t=1.858, 0.896; P=0.072, 0.377). After four-week treatment, FMA and MBI in both groups improved significantly (P<0.05); the difference between the experimental group [(27.56±15.68) and (73.55±8.72) points] and the control group [(17.67±6.73) and (65.33±9.20) points] was statistically significant (t=2.459, 2.751; P=0.019, 0.009).ConclusionsThe end-traction upper limb rehabilitation training system can significantly improve the upper limb motor function of patients with upper limb motor dysfunction after stroke and improve the patients’ daily life ability. It is worthy of clinical promotion and application.
ObjectiveTo explore the effect of early graded respiratory severe rehabilitation training for patients with mechanical ventilation under a multidisciplinary model.MethodsTwo hundred and thirty-six patients were surveyed, who were hospitalized in the intensive care unit of the First Affiliated Hospital of Anhui Medical University from June 3, 2019 to March 31, 2020. They were randomly divided into an observation group and a control group, with 118 patients in each group. The observation group received rehabilitation training using early graded rehabilitation training under the mode of multidisciplinary cooperation, while the control group received routine respiratory rehabilitation training. Diaphragmatic excursion (DE) and diaphragmatic thickening fraction (DTF) of the patients before ventilator weaning were measured by ultrasound. The differences of DE, DTF, peak expiratory flow (PEF), maximal inspiratory pressure (MIP), success rate of withdrawal, duration of mechanical ventilation and intensive care unit (ICU) stay between the two groups were recorded and compared.ResultsAll evaluation indexes were statistically significant between the observation group and the control group (all P<0.05). There were interaction between oxygenation index, PEF, MIP, Acute Physiology and Chronic Health Score, Clinical Pulmonary Infection Score and recovery time.ConclusionRehabilitation training on early graded severe respiratory diseases under a multidisciplinary model can improve the respiratory function of patients on mechanical ventilation and shorten the duration of mechanical ventilation and ICU stay.