ABSTRACT
Objective@#To explore the topological abnormality of brain metabolic network in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and compare it with the topology of brain metabolic network in patients with Parkinson′s disease (PD).@*Methods@#The 18F-fluorodeoxyglucose (FDG) PET brain images of 19 patients with iRBD diagnosed with polysomnography (PSG) (iRBD group; 15 males, 4 females, average age: 64.9 years), 19 patients with PD (PD group; 12 males, 7 females, average age: 62.2 years) and 19 gender and age-matched healthy controls (HC group; 15 males, 4 females, average age: 63.1 years) in Huashan Hospital from September 2014 to June 2015 were retrospectively analyzed. According to the complex brain network method based on graph theory, the brain metabolic networks of each group was constructed and the network parameters (clustering coefficient, characteristic path length, local efficiency, global efficiency and small-world property, etc) were evaluated quantitatively. The 500 times non-parametric permutation test was used to determine the differences in network parameters between groups.@*Results@#The brain metabolic networks of iRBD group and PD group both had abnormal topological structure, which showed that the characteristic path length (for example, when sparsity=34%, HC vs iRBD vs PD groups: 1.517 vs 1.552 vs 1.561) and local efficiency (for example, when sparsity=30%, HC vs iRBD vs PD groups: 0.802 vs 0.824 vs 0.831) were significantly increased (both P<0.05), the global efficiency (for example, when sparsity=36%, HC vs iRBD vs PD groups: 0.672 vs 0.658 vs 0.656) was significantly decreased (P<0.05). The topology was more aggravated in PD group compared with that in iRBD group.@*Conclusion@#The graph-based complex brain network analysis can reveal the abnormal topological structure of the brain metabolic network in which iRBD progresses to PD.
ABSTRACT
Objective To explore the topological abnormality of brain metabolic network in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and compare it with the topology of brain metabolic network in patients with Parkinson's disease (PD).Methods The 18F-fluorodeoxyglucose (FDG) PET brain images of 19 patients with iRBD diagnosed with polysomnography (PSG) (iRBD group;15 males,4 females,average age:64.9 years),19 patients with PD (PD group;12 males,7 females,average age:62.2 years) and 19 gender and age-matched healthy controls (HC group;15 males,4 females,average age:63.1 years) in Huashan Hospital from September 2014 to June 2015 were retrospectively analyzed.According to the complex brain network method based on graph theory,the brain metabolic networks of each group was constructed and the network parameters (clustering coefficient,characteristic path length,local efficiency,global efficiency and small-world property,etc) were evaluated quantitatively.The 500 times non-parametric permutation test was used to determine the differences in network parameters between groups.Results The brain metabolic networks of iRBD group and PD group both had abnormal topological structure,which showed that the characteristic path length (for example,when sparsity =34％,HC vs iRBD vs PD groups:1.517 vs 1.552 vs 1.561) and local efficiency (for example,when sparsity=30％,HC vs iRBD vs PD groups:0.802 vs 0.824 vs 0.831) were significantly increased (both P＜0.05),the global efficiency (for example,when sparsity =36％,HC vs iRBD vs PD groups:0.672 vs 0.658 vs 0.656) was significantly decreased (P＜0.05).The topology was more aggravated in PD group compared with that in iRBD group.Conclusion The graph-based complex brain network analysis can reveal the abnormal topological structure of the brain metabolic network in which iRBD progresses to PD.
ABSTRACT
In aging society the development of non-invasive continuously blood pressure monitors which are suitable for homes, communities and nursing homes has a wide range of applications. This paper proposes a non-invasive continuously blood pressure monitoring based on wearable device which uses MSP430F5529 as the central processor. The design is divided into signal acquisition module, central control module, display module, power supply module and host computer module. The experimental results showed that DBP (375/390, 96.15%) and SBP estimation values (377/390, 96.67%) are in 95% confidence interval, which means our design passes Bland-Altman test with high accuracy and stability.