The sensitivity of near-infrared spectroscopy (NIRS) to evoked brain activity is reduced by physiological interference in at least two locations: 1. the superficial scalp and skull layers, and 2. in brain tissue itself. These interferences are generally termed as "global interferences" or "systemic interferences," and arise from cardiac activity, respiration, and other homeostatic processes. We present a novel method for global interference reduction and real-time recovery of evoked brain activity, based on the combination of a multiseparation probe configuration and adaptive filtering. Monte Carlo simulations demonstrate that this method can be effective in reducing the global interference and recovering otherwise obscured evoked brain activity. We also demonstrate that the physiological interference in the superficial layers is the major component of global interference. Thus, a measurement of superficial layer hemodynamics (e.g., using a short source-detector separation) makes a good reference in adaptive interference cancellation. The adaptive-filtering-based algorithm is shown to be resistant to errors in source-detector position information as well as to errors in the differential pathlength factor (DPF). The technique can be performed in real time, an important feature required for applications such as brain activity localization, biofeedback, and potential neuroprosthetic devices.

Background China’s smart home for elderly care emerged in 2008, and had went through four developmental stages which consists of seed stage, start-up stage, development stage and popularization stage. Main text The status quo and development of smart home for elderly care in China is reviewed, and suggestions are provided on how to further develop China’s smart home for elderly care. The focus of China’s policies on smart home for elderly care were different during those four developmental stages. Compared with Western countries, China’s smart home for elderly care is a policy-driven product rather than technology-driven or demand-driven one. In addition, it is quasi-public goods rather than private goods. These unique characteristics of China’s smart home for elderly care not only become the driving force of its rapid development, but also bring many challenges to its development, such as the insufficient demand, the disorderly development, and the waste of public and private resources. Conclusions Although great progress has been made in China’s smart home care, much efforts are still needed to further advance its development. The technical standards for the elderly care services should be formulated as soon as possible and the existing public and private smart home for elderly care platforms should be combined. Enterprises involved in smart home care services should be encouraged to develop new technologies to reduce the cost of products and services provided by smart home for elderly care.

A preliminary Indoor Air Quality study was performed in 26 residential homes in 6 cities in different climate zones in China. In Chinese urban environments, coal gas and natural gas are used as the main fuels for cooking. Analysis of the results employed the ratio of living room to kitchen (L/K) pollutant concentrations and the correlation of their levels to assess the transport of pollutants indoors. Sources in the kitchen affect living room concentrations of SO 2 , NO, NO 2 , and CO, less so that of CO 2 levels and weakly of PM 10 . Among all the pollutants, SO 2 has the minimum 0.88 L/K ratio value, and maximum correlation value, R 2 ¼ 0.89; on the other hand, PM 10 has the maximum L/K ratio value, 1.20 and minimum R 2 -value, 0.55, which means that PM 10 is mostly influenced by activities and other factors that do not take place in the kitchen. Concentrations of SO 2 differed significantly depending on the fuel type used for cooking with coal gas producing 87.6% higher SO 2 concentrations than natural gas. Concentrations of CO 2 and PM 10 were the same regardless of gas type. The type of ventilation was found to influence pollutant concentrations with a mechanical exhaust system showing higher efficiency than a natural ventilation system in exhausting pollutants. The period and style of cooking also affected concentrations of pollutants in the kitchen.

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