Cipher Skin’s core technology is derived from the following principles.
- Any 3-dimensional shape that requires monitoring via ambient or interactive sensor can be tessellated – i.e. covered in a repeated geometric pattern of identical interlocking shapes – when the surface can be approximated in two dimensions.
2. Whatever monitoring is required can be fit to task from existing commercial components. Our initial offerings are centered on biometric (movement, heart rate, blood oxygen saturation, etc.) and industrial (strain, vibration, acoustic, etc.) monitoring.
3. Our existing IP allows us to collect measurements simultaneously, on the same system clock, which allows excellent speed of access and feedback, as well as opportunities for straightforward integration between signals.
4. Sensor output can be collated, analyzed as a time series by simple linear models, and used to build predictive models of events relevant to the monitored environment (injury, structural or catastrophic failure, etc.)
Any simple 3-dimensional surface can be trivially transformed into planes which provide an active monitoring area. For instance, an arm might be approximated as the curved surface of a cylinder using the formula A=2πrh. The surface area determines the geometric shape of the primary Cipher Mesh sensor infrastructure and the distance between sub-sensors. The relationship between shape and surface area determines the number of segments in a single cell, hence the number of repeating geometric cells over a given area.
Next, the geometric pattern determines the maximum number of sub-sensors that can be integrated. The sub-sensors are placed at the nodes between cell segments. The type of sensors embedded are determined by use case – for instance, pipeline monitoring needing acoustics for flow versus a shirt needing ekg pads for heart rate.
Frequency of sensor placement is also determined by use case – oil pipes might need thermal sensors placed every 10 feet where water pipes might only need thermal sensors every 100 feet.
We can characterize the sensor integration throughout the entire surface area of an object based on the shape of the primary sensor array – as shown below –, the total surface area of the object being monitored and the specific sensor requirements dictated by the application.
Ultimately, the objective is to integrate the useful number of sensors quickly and efficiently into a design without having to design a use-case specific circuit. Finally, a passthrough is connected to each node without a sensor. The passthrough allows transmission of current and data between segments.
Given the above, consider a body as a series of limb cylinders. We can examine how this body in space interacts with the world around it perpetually and in real time, as Cipher Mesh core technology allows us to monitor multiple metrics simultaneously, on the same system clock. A variety of monitoring applications are presented, which have relevant suites of monitored variables.
Retrieved signals allow, in increasing order of complexity:
– accurate monitoring of the desired shape as a time series (1)
– complex instantaneous measurements by combining signals (2)
(for instance, measuring electrical to vascular lag as a proxy for vascular stiffness, or monitoring wall thickness and ambient temperature to determine the brittleness of a concrete section of bridge)
– the integration of (1) and (2) into near-instantaneous monitoring or user feedback
– the eventual acquisition of a sufficient database of integrated signals to form models for catastrophic events (i.e. via ANN, SVM, etc.) predicted in advance.
When the segment with nodes is applied around a cylinder, we have a parabolic 3-dimensional shape. The shape is able to monitor multiple types of strain across multiple planes, as well as temperature, flow and expansion. All measurements are on the same system clock and the output is sent to a common table.