For speech detection in Parkinson’s patients, we proposed a method based on time-frequency domain gradient statistics to analyze speech disorders of Parkinson’s patients. In this method, speech signal was first converted to time-frequency domain (time-frequency representation). In the process, the speech signal was divided into frames. Through calculation, each frame was Fourier transformed to obtain the energy spectrum, which was mapped to the image space for visualization. Secondly, deviations values of each energy data on time axis and frequency axis was counted. According to deviations values, the gradient statistical features were used to show the abrupt changes of energy value in different time-domains and frequency-domains. Finally, KNN classifier was applied to classify the extracted gradient statistical features. In this paper, experiments on different speech datasets of Parkinson’s patients showed that the gradient statistical features extracted in this paper had stronger clustering in classification. Compared with the classification results based on traditional features and deep learning features, the gradient statistical features extracted in this paper were better in classification accuracy, specificity and sensitivity. The experimental results show that the gradient statistical features proposed in this paper are feasible in speech classification diagnosis of Parkinson’s patients.
Objective To review the progress of perioperative treatments for patients of Parkinson’s disease and hip fractures. Methods The related literature of treatments for patients of Parkinson’s disease and hip fractures were reviewed and analyzed from the aspects such as the perioperative management, selection of operation ways, and prognosis. Results The patients of Parkinson’s disease are more likely to sustain hip fractures because of postural instability and osteoporosis. The perioperative treatments for patients of Parkinson’s disease and hip fractures should be determined by orthopedists, neurologist, anesthesiologist, and physical therapist. There is still controversy about the selection of operation and surgical approach. And the prognosis of patients of Parkinson’s disease and hip fractures are associated with the severity of Parkinson’s disease. Conclusion There are few clinical studies about the patients of Parkinson’s disease and hip fractures. The mid-term and long-term functional outcomes of patients of Parkinson’s disease and hip fractures are unsufficient. And the best treatments of patients of Parkinson’s disease and hip fractures need to be further explored.
Evidence has been retrieved through MEDLINE and Cochrane Libray about the treatment for patients with advanced Parkinson’s disease who suffered from on-off, dyskinesia and depression after chronic use of L-dopa. All of the evidence has been evaluated. Methods of evidence-based treatment were drawn up according to the evidence, clinciams’ experiences and patients’ preferences. All symptoms of the patient have been improved obviously.
Motor dysfunction is the main clinical symptom and diagnosis basis of patients with Parkinson’s disease (PD). A total of 30 subjects were recruited in this study, including 15 PD patients (PD group) and 15 healthy subjects (control group). Then 5 wearable inertial sensor nodes were worn on the bilateral upper limbs, lower limbs and waist of subjects. When completing the 6 paradigm tasks, the acceleration and angular velocity signals from different parts of the body were acquired and analyzed to obtain 20 quantitative parameters which contain information about the amplitude, frequency, and fatigue degree of movements to assess the motor function. The clinical data of the two groups were statistically analyzed and compared, and then Back Propagation (BP) Neural Network was used to classify the two groups and predict the clinical score. The final results showed that most of the parameters had significant difference between the two groups, ten times of 5-fold cross validation showed that the classification accuracy of the BP Neural Network for the two groups was 90%, and the predictive accuracy of Hoehn-Yahr (H-Y) staging and unified PD rating scale (UPDRS) Ⅲ score of the patients were 72.80% and 68.64%, respectively. This study shows the feasibility of quantitative assessment of motor function in PD patients using wearable sensors, and the quantitative parameters obtained in this paper may have reference value for future related research.
Methods for achieving diagnosis of Parkinson’s disease (PD) based on speech data mining have been proven effective in recent years. However, due to factors such as the degree of disease of the data collection subjects and the collection equipment and environment, there are different categories of sample aliasing in the sample space of the acquired data set. Samples in the aliased area are difficult to be identified effectively, which seriously affects the classification accuracy of the algorithm. In order to solve this problem, a partition bagging ensemble learning is proposed in this article, which measures the aliasing degree of the sample by designing the the ratio of sample centroid distance metrics and divides the training set into multiple subsets. And then the method of transfer training of misclassified samples is used to adjust the results of subset partitioning. Finally, the optimized weights of each sub-classifier are used to integrate the test results. The experimental results show that the classification accuracy of the proposed method is significantly improved on two public datasets and the increasement of mean accuracy is up to 25.44%. This method not only effectively improves the classification accuracy of PD speech dataset, but also increases the sample utilization rate, providing a new idea for the diagnosis of PD.
Objective To assess the changes in depression symptoms in patients with Parkinson’s disease (PD) receiving combined treatment of deep brain stimulation (DBS) and antiparkinsonian drug therapy (DT) compared with under DT alone. Methods Related literature was retrieved from electronic databases, including PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, Wanfang Data, and VIP databases. Stata 14.0 software was used for statistical analysis. Network meta-analysis was performed using frequentist model to compare different interventions with each other. Results Five cohort studies and seven randomized controlled trials (RCTs) were included. The total number of participants was 1241. Assessed by the Beck Depression Inventory (BDI) score as the primary outcome, patients who received DT alone showed worse outcome in depression as compared to those who received subthalamic nucleus (STN)-DBS plus DT [standardized mean difference (SMD)=0.30, 95% confidence interval (CI) (0.01, 0.59), P<0.05], and there was no significant difference between the patients receiving globus pallidus interna (GPi)-DBS plus DT and those receiving STN-DBS plus DT [SMD=–0.12, 95%CI (–0.41, 0.16), P>0.05] or those receiving DT alone [SMD=–0.42, 95%CI (–0.84, 0.00), P>0.05]. Assessed by BDI-Ⅱ as the primary outcome, patients who received DT alone showed worse outcome in depression than those who received STN-DBS plus DT [SMD=0.29, 95%CI (0.05, 0.54), P<0.05]; compared with STN-DBS plus DT and DT alone, GPi-DBS plus DT was associated with better improvement in depression [SMD=–0.26, 95%CI (–0.46, –0.06), P<0.05; SMD=–0.55, 95%CI (–0.88, –0.23), P<0.05]. The ranking results of surface under the cumulative ranking curves showed that DBS plus DT had a better superiority in depression symptoms, and GPi-DBS was better than STN-DBS. Conclusion Compared with DT, STN-DBS plus DT is more likely to improve the depressive symptoms of PD patients, and GPi-DBS may be better than STN-DBS.
People with Parkinson’s disease (PD) exhibit multi-system damaged. Medication mainly targets impairments related to dopaminergic lesions. Moreover, in later stages of the disease, medication becomes less effective. Rehabilitation therapy is believed that it can improve multiple functional disorders, including myotonia, bradykinesia, and postural gait abnormalities. It not only reduces the severity of non-motor symptoms and improves the quality of life in PD patients, but also delays the development of PD and improves the activity of daily life of patients. This article summarizes the progress of rehabilitation assessment and the therapy of PD.
Dysphagia is a common non-motor symptom in Parkinson’s disease (PD), with a high incidence and insidious progression. It can lead to complications such as dehydration, malnutrition, aspiration pneumonia, and even death, seriously affecting the quality of life and prognosis of patients. Therefore, early screening, assessment, and intervention are crucial for improving the quality of life and prognosis of PD patients with dysphagia. This article mainly reviews the risk factors and management strategies of dysphagia in PD, with the aim of providing a reference for healthcare professionals to conduct subsequent evaluations and develop targeted interventions.
Parkinson’s disease is a common neurodegenerative disorder with continuously rising incidence rates. Existing pharmacological treatments have complications and cannot halt disease progression. Transcranial focused ultrasound stimulation (tFUS), as a novel neuromodulation technology, demonstrates unique advantages in Parkinson’s disease treatment. tFUS exerts multiple effects through mechanical mechanisms at multiple levels, including protecting dopaminergic neurons, regulating neurotransmitter systems, and improving neural circuit function. Preclinical studies have confirmed its potential in improving both motor and non-motor symptoms, and early clinical studies have shown good safety profiles. However, the clinical translation of tFUS still faces challenges such as parameter optimization and individualized treatment protocols, requiring validation of long-term efficacy through large-scale clinical trials.
The application of dopamine agonists in Parkinson’s disease has been a hot topic in recent years. Can dopamine receptor agonists serve as the initial drugs for Parkinson’s disease? Does it improve the natural history of patients? Has it neuroprotective role? When and how to use dopamine receptor agonists? This article provides evidence on the pros and cons of dopamine receptor agonists in the treatment of Parkinson’s disease for helping clinical decision making.