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The identification of neural stem and progenitor cells (NPCs) by in vivo brain imaging could have important implications for diagnostic, prognostic, and therapeutic purposes. We describe a metabolic biomarker for the detection and quantification of NPCs in the human brain in vivo. We used proton nuclear magnetic resonance spectroscopy to identify and characterize a biomarker in which NPCs are enriched and demonstrated its use as a reference for monitoring neurogenesis. To detect low concentrations of NPCs in vivo, we developed a signal processing method that enabled the use of magnetic resonance spectroscopy for the analysis of the NPC biomarker in both the rodent brain and the hippocampus of live humans. Our findings thus open the possibility of investigating the role of NPCs and neurogenesis in a wide variety of human brain disorders.

In the last decade, the research on and the technology for outdoor tracking have seen an explosion of advances. It is expected that in the near future we will witness similar trends for indoor scenarios where people spend more than 70% of their lives. The rationale for this is that there is a need for reliable and high-definition real-time tracking systems that have the ability to operate in indoor environments, thus complementing those based on satellite technologies such as GPS. The indoor environments are very challenging and, as a result, a large variety of technologies have been proposed for coping with them, but no legacy solution has emerged yet. This paper presents a survey on indoor wireless tracking of mobile nodes from a signal processing perspective. It can be argued that the indoor tracking problem is more challenging than the one on indoor localization. The reason is simple -from a set of measurements one has to estimate not one location but a series of correlated locations of a mobile node. The paper illustrates the theory, the main tools and the most promising technologies for indoor tracking. New directions of research are also discussed.Index Terms-Indoor tracking, simultaneous localization and mapping, Bayesian filtering, data fusion, technologies for tracking. I. INTRODUCTIONIndoor real time locating systems (RTLS) have been gaining relevance due to the widespread advances of devices and technologies and the necessity for seamless solutions in location-based services. An important component of RTLS is indoor tracking where objects, vehicles or people (in the sequel referred to as mobile nodes) are tracked within a building or any enclosed structure. Examples include tracking of products through manufacturing lines, first-responder navigation, asset