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Parkinson's disease (PD) is a chronic progressive neurodegenerative disease that is clinically manifested by a triad of cardinal motor symptoms - rigidity, bradykinesia and tremor - due to loss of dopaminergic neurons. The motor symptoms of PD become progressively worse as the disease advances. PD is also a heterogeneous disease since rigidity and bradykinesia are the major complaints in some patients whereas tremor is predominant in others. In recent years, many studies have investigated the progression of the hallmark symptoms over time, and the cardinal motor symptoms have different rates of progression, with the disease usually progressing faster in patients with rigidity and bradykinesia than in those with predominant tremor. The current treatment regime of dopamine-replacement therapy improves motor symptoms and alleviates disability. Increasing the dosage of dopaminergic medication is commonly used to combat the worsening symptoms. However, the drug-induced involuntary body movements and motor complications can significantly contribute to overall disability. Further, none of the currently-available therapies can slow or halt the disease progression. Significant research efforts have been directed towards developing neuroprotective or disease-modifying agents that are intended to slow the progression. In this article, the most recent clinical studies investigating disease progression and current progress on the development of disease-modifying drug trials are reviewed.

The concept of kinematic synergies is proposed to address the dimensionality reduction problem in control and coordination of the human hand. This paper develops a method for extracting kinematic synergies from joint-angular-velocity profiles of hand movements. Decomposition of a limited set of synergies from numerous movements is a complex optimization problem. This paper splits the decomposition process into two stages. The first stage is to extract synergies from rapid movement tasks using singular value decomposition (SVD). A bank of template functions is then created from shifted versions of the extracted synergies. The second stage is to find weights and onset times of the synergies based on l(1) -minimization, whose solutions provide sparse representations of hand movements using synergies.

It has been reported that the pulse transit time (PTT), the interval between the peak of the R-wave in electrocardiogram (ECG) and the fingertip photoplethysmogram (PPG), is related to arterial stiffness, and can be used to estimate the systolic blood pressure (SBP) and diastolic blood pressure (DBP). This phenomenon has been used as the basis to design portable systems for continuously cuff-less blood pressure measurement, benefiting numerous people with heart conditions. However, the PTT-based blood pressure estimation may not be sufficiently accurate because the regulation of blood pressure within the human body is a complex, multivariate physiological process. Considering the negative feedback mechanism in the blood pressure control, we introduce the heart rate (HR) and the blood pressure estimate in the previous step to obtain the current estimate. We validate this method using a clinical database. Our results show that the PTT, HR and previous estimate reduce the estimated error significantly when compared to the conventional PTT estimation approach (p<0.05).

C Corporate researCh Centers, universities, power equipment vendors, end users, and other market participants around the world are beginning to explore and consider the use of dc in future transmission and distribution system applications. recent developments and trends in electric power consumption indicate an increasing use of dc-based power and constantpower loads. in addition, growth in renewable energy resources requires dc interfaces for optimal integration. a strong case is being made for intermeshed ac and dc networks, with new concepts emerging at the medium-voltage (mv) level for mvdc infrastructure developments.at the turn of the 20th century, the use of ac transmission, as opposed to dc, was a justifiable decision for many reasons. Looking toward the future of transmission and distribution, this decision must be reevaluated in light of the changes taking place throughout the u.s. electric grid at all levels: generation, transmission, distribution, and end use. in 2006, electric power research institute (epri) presented a number of valid arguments that strengthened the case for dc infrastructure in the 21st century. modern advances in the transportation industry have often come through the application of electronics (electric vehicles and magnetic levitation trains, for example). these innovations utilize dc power, requiring an ac-to-dc conversion within the current grid infrastructure. the microgrid, composed of distributed generation (such as photovoltaic systems) and energy storage systems that produce dc power, is a key emerging technology. Finally, utilities are trying to develop solutions for integrating renewable energy with storage devices to deliver dc power. these advances will make utility-scale energy storage more economical and efficient.power electronics technology is an efficient, powerful, and reliable solution for integrating large amounts of renewable generation into existing grid infrastructure. increased renewable integration with aggressive growth targets is a mandate set forth by the u.s. government, with a deadline in 2030. developments in the area of power electronics, including the application of novel semiconductor devices and materials, have unlocked the potential for higher-capacity, faster-switching, lower-loss conversion, inversion, and rectification devices. in recent years, the advent of silicon carbide solid-state electronic devices, which have lower switching and conduction losses compared with silicon devices, has made dc-ac conversion more promising in the near-term time frame. virtually all voltage and current ratings are possible by utilizing series and parallel combinations of discrete semiconductors. all of these factors are combining to form an opportunity for the development and further deployment of dc technology throughout the electric grid at all levels.

The AI technology can automatically detect foods from low-quality, wearable camera-acquired real-world egocentric images with reasonable accuracy, reducing both the burden of data processing and privacy concerns.

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