This paper addresses the current issue of energy harvesting from various physical sources of passive energy, such as vibrations. The aim of the paper is to present a digital signal processing architecture that is energy efficient and robust, and particularly suitable for wearable biomedical sensors. The authors discuss their architecture, and present two applications to be used in testing it.

The main architecture of concern here is the sensor digital signal processing (DSP) architecture, which consists of three main components and a buffer. The first component is a distributed arithmetic unit. The output of this unit is written into the buffer, and into a nonlinear-short linear filter unit, which also writes to the buffer. The two outcomes are read from the buffer by a classification microcontroller unit. The implementation of the sensor DSP architecture is discussed, followed by extensions for the next generation of DSPs for energy harvesting. One particular technique that is explained is self-timed circuit design. One of the advantages of this design is the ability to cope well with power-on and power-down cycles that may occur more frequently, since the power being harvested is dependent on vibrations. Regulating energy variability is an important issue for application of this type of research.

The only negative of this paper is that the title gives the impression that different architectures are being considered. What are the different types of DSP architectures in addition to sensor DSP? What are the different types of sensor DSP architectures? Reading the paper gives an impression that the authors are presenting their own development of one particular architecture. In addition, it is not clear how the work presented relates or builds on previous work done by the authors and others in the context of developing the architecture. There is a very short list of references.