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BACKGROUND AND OBJECTIVE: Deep brain stimulation (DBS) is an effective treatment for a number of neurological diseases, especially for the advanced stage of Parkinson's disease (PD). Objective assessment of patients' motor symptoms is crucial for accurate electrode targeting and treatment. Existing approaches suffer from subjective variability or interference with voluntary motion. This work is aimed to establish an objective assessment system to quantify bradykinesia in DBS surgery. METHODS: Based on the analysis of the requirements for intraoperative assessment, we developed a system with non-contact measurement, online movement feature extraction, and interactive data analysis and visualization. An optical sensor, Leap Motion Controller (LMC), was taken to detect hand movement in three clinical tasks. A graphic user interface was designed to process, compare and visualize the collected data and assessment results online. Quantified movement features include amplitude, frequency, velocity, their decrement and variability, etc. Technical validation of the system was performed with a motion capture system (Mocap), with respect to data-level and feature-level accuracy and reliability. Clinical validation was conducted with 20 PD patients for intraoperative assessments in DBS surgery. Treatment responses with respect to the bradykinesia movement features were analyzed. Single case analysis and group statistical analysis were performed to examine the differences between preoperative and intraoperative performance, and the correlation between the clinical ratings and the quantified assessment was analyzed. RESULTS: For the movements measured by LMC and Mocap, the average Pearson's correlation coefficient was 0.986, and the mean amplitude difference was 2.11 mm. No significant difference was found for all movement features quantified by LMC and Mocap. For the clinical tests, key movement features showed significant differences between the preoperative baseline and intraoperative performance when the brain stimulation was ON. The assessment results were significantly correlated with the MDS-UPDRS clinical ratings. CONCLUSIONS: The proposed non-contact system has established itself as an objective intraoperative assessment, analysis, and visualization tool for DBS treatment of Parkinson's disease.
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Estimulação Encefálica Profunda , Doença de Parkinson , Estimulação Encefálica Profunda/métodos , Humanos , Hipocinesia/terapia , Organotiofosfatos , Doença de Parkinson/diagnóstico , Doença de Parkinson/cirurgia , Reprodutibilidade dos TestesRESUMO
INTRODUCTION: Gait disorders are common in patients with Parkinson's disease (PD), and objective, quantifiable, and portable evaluation methods are needed in clinical practice. We assessed the differences in gait characteristics between patients with PD and healthy controls (HCs) using two-dimensional (2D) video and explored the diagnostic value of 2D video for early-stage PD. METHODS: Sixty-eight patients with PD and 48 HCs were recruited. All participants walked a standard 5-m track while recorded using mobile phones. The differences in gait characteristics between the groups and gait parameters of patients with early-stage PD were analyzed. Receiver operating characteristic analysis was used to evaluate the discrimination activity of gait parameters. RESULTS: Compared with HCs, patients with PD had shorter step length (S/M, p < 0.001/0.001), faster cadence (p = 0.044), slower walking speed (p < 0.001), smaller arm-swing angle (S/M, p < 0.001/0.001), slower arm-swing velocity (S/M, p < 0.001/0.001), and greater variability and asymmetry. The patients with early-stage PD had similar characteristics. After combined step length and variability and asymmetry of arm-swing angle, diagnostic sensitivity and specificity reached 84.6% and 89.6%, respectively, and an area under the curve of 0.91 (0.84-0.97). CONCLUSION: We proposed a new method to improve the sensitivity of early-stage PD diagnosis using 2D video, which, as a portable and objective method, could be used to evaluate gait disorders in PD, including in early-stage PD. Combined diagnostic analysis of step length and variability and asymmetry of arm-swing angle could improve the sensitivity of PD diagnosis and was helpful in distinguishing patients with early-stage PD from HCs.
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Transtornos Neurológicos da Marcha , Doença de Parkinson , Braço , Marcha , Transtornos Neurológicos da Marcha/diagnóstico , Transtornos Neurológicos da Marcha/etiologia , Humanos , Doença de Parkinson/complicações , Doença de Parkinson/diagnóstico , CaminhadaRESUMO
BACKGROUND: Deep brain stimulation (DBS) has proved effective for Parkinson's disease (PD), but the identification of stimulation parameters relies on doctors' subjective judgment on patient behavior. METHODS: Five PD patients performed 10-meter walking tasks under different brain stimulation frequencies. During walking tests, a wearable functional near-infrared spectroscopy (fNIRS) system was used to measure the concentration change of oxygenated hemoglobin (â³HbO2) in prefrontal cortex, parietal lobe and occipital lobe. Brain functional connectivity and global efficiency were calculated to quantify the brain activities. RESULTS: We discovered that both the global and regional brain efficiency of all patients varied with stimulation parameters, and the DBS pattern enabling the highest brain efficiency was optimal for each patient, in accordance with the clinical assessments and DBS treatment decision made by the doctors. CONCLUSIONS: Task fNIRS assessments and brain functional connectivity analysis promise a quantified and objective solution for patient-specific optimization of DBS treatment. TRIAL REGISTRATION: Name: Accurate treatment under the multidisciplinary cooperative diagnosis and treatment model of Parkinson's disease. Registration number is ChiCTR1900022715. Date of registration is April 23, 2019.
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Using "human-in-the-loop" (HIL) optimization can obtain suitable exoskeleton assistance patterns to improve walking economy. However, there are differences in these patterns under different gait conditions, and currently most HIL optimizations use metabolic cost, which requires long periods to be estimated for each control law, as the physiological objective to minimize. We aimed to construct a muscle-activity-based cost function and to find the appropriate initial assistance patterns in HIL optimization of multi-gait ankle exoskeleton assistance. One healthy subject walked assisted by an ankle exoskeleton under nine gait conditions and each condition was the combination of different walking speeds, ground slopes and load weights. Ten assistance patterns were provided for the subject under each gait condition. Then we constructed a cost function based on surface electromyography signals of four lower leg muscles and select the muscle weight combination by using particle swarm optimization algorithm to compose the cost function with maximum differences between different assistance patterns. The mean weights of medial gastrocnemius, lateral gastrocnemius, soleus and tibialis anterior activity under all gait conditions are 0.153, 0.104, 0.953 and 0.145, respectively. Then we verified the effectiveness of this cost function by optimization and validation experiments conducted on four subjects. Our results are expected to guide the selection of muscle-activity-based cost functions and improve the time efficiency of HIL optimization.
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Exoesqueleto Energizado , Robótica , Algoritmos , Tornozelo , Articulação do Tornozelo , Fenômenos Biomecânicos , Eletromiografia , Marcha , Humanos , Músculo Esquelético , CaminhadaRESUMO
OBJECTIVE: To investigate the epidemiological features of child and adolescent (≤18 years old) patients managed for traumatic skull fractures (TSKFs) and associated traumatic brain injury (TBI). DESIGN: 393 Patients who were children and adolescent who had TSKFs admitted to our university affiliated hospitals between January 2003 and December 2010. The incidence and patterns were summarized with respect to different age group, admission time and etiology. SETTING: Two university-affiliated hospitals from January 2003 to May 2010. RESULTS: The most common etiologies were motor vehicle collisions (MVCs) (166, 42.2%) and high fall (101, 25.7%). The most common skull fracture sites were parietal fractures (n=111, 28.2%) and basilar skull fracture (n=111, 28.2%). A total of 300 (76.3%) patients suffered TBI and 23 (5.9%) patients suffered OCI. The most common intracranial hemorrhage was epidural hemorrhage (n=94, 23.9%). The frequencies of emergency admission, medical insurance and associated injuries were 56.2% (n=221), 22.4% (n=88) and 37.2% (n=146). The frequencies of TBI and associated injuries were significantly increased from 53.45% to 76.3% and from 6.9% to 41.6% with age, respectively. CONCLUSIONS: MVCs were the most common etiologies. Parietal and basilar skull fractures, epidural hemorrhages were the most common fracture sites and intracranial hemorrhage.