A Simple Iterative Algorithm for Wellness Applications

The concept of "wellness mobile" is one wherein wireless handheld devices such as cell phones are equipped with "wellness monitoring," thereby enabling real-time self-wellness monitoring by the cell phone user. However, this new technology is still in its infancy, and developing quantifiable measures of wellness and designing intelligent monitoring systems is quite challenging. The overriding purpose of this paper is to propose a simple wellness monitoring algorithm. The novel algorithm iteratively computes and tracks the variations in clusters of biometric measurements aiding in effective wellness management. Stress is a key indicator of wellness in human beings, and is widely regarded as a prime contributor to performance degradation and errors during various human activities. The proposed algorithm tracks the deviations in clusters of skin temperatures measurements during different activities to infer the stress states in humans. The advantage is that this simple algorithm can be implemented on handheld devices by deploying existing biometric sensors that are available in most smart phones today. This will provide cellular phones users an application to monitor their stress states easily and consistently in a non-invasive way because a stressed-out lifestyle is rarely a healthy one.