## 2 Background  
At its most basic level, telemetry encapsulates data and allows measurements remotely, and sends those measurements to a location where they are of most use. Medical sensors are available to take measurements of such biometric data such as Temperature, Heart rate, Blood pressure, Respiration (breathing) rate, Blood oxygen concentration and Blood sugar concentration. These sensors can all be used to take discrete readings which lend themselves to digital encoding. As a result, many of the sensors above could be encoded within an SMS. However, there are also more \"detailed\" types of medical sensors, such as the electrocardiogram (ECG), which plots an entire cardiac activity cycle in the heart. This more detailed type of sensor produces a vast amount of data, and sensors like ECG's are typically used to produce continuous, analogue data. When dealing with a human body, the ranges of data we expect to receive can be set with relative accuracy. Table 1 shows the ranges of data for a selection of vital signs in the human body. By defining the ranges of data, we can define the size of the data element we must use to record the data. For example, if dealing with data in the range 0-255, the value is recordable in a single octet. If the range is just one greater, 0-256, we require an extra bit, and depending on the data coding scheme we use, this may mean we will possibly require the use of an entire extra octet. The challenge is how to use these types of data, and varying sample rates, to encode useful information into the data space provided by SMS. There are many different sorts of data which can make up a set of medical telemetry. However, not all this data is suitable for transmission in a mechanism such as SMS. An SMS message is a packetized collection of 140 octets (1,120 bits) of binary data ordered into an extremely well defined transport mechanism. In recent years, SMS has become an integral part of our daily lives and is now a virtually ubiquitous service offered by mobile carriers worldwide. Furthermore, modern SMS has introduced the multi-part or concatenated message, where a single SMS message can theoretically consist of up to 255 sequentially chained SMS packets [16]. Although theoretically possible to chain 256 messages together into a single concatenated SMS, the nature of the transmission mechanism for SMS messaging does not necessarily facilitate such large messages. Issues such as the fact that SMS may not be delivered (due to their internal validity period), and the fact that the GSM network does not guarantee that SMS are delivered to the recipient in the order in which they were sent [17] all impact on the maximum practical size of concatenated SMS messages. Thus, issues around delivery reliability, validity periods of messages, and the time-to-live for an SMS message, the delivery guarantees not made by the network, and the lack of formal delivery receipts must all be considered when examining potential applications for SMS. Furthermore, the security of information must be a concern in environments where personal or privileged data is being transferred. Therefore, for SMS to be used as the telemetry data transmission protocol, each of these issues needs to be examined, and an appropriate mitigation is implemented. An important technical challenge is the apparent issues of multi-sensor medical data fusion, system optimization, real-time wireless transmission, and information security. A medical telemetry data set may consist of data from different sensors. However, we could consider a case where a number of patients are monitored at the same location. In this case, a single telemetry dataset might well contain discrete data from sensors on many different patients. To cater for such situations, it was our intention to create a data coding scheme to cater for the following scenarios: (i) Single patient, single sensor; (ii) Single patient, multiple sensors; (iii) Multiple patient, multiple sensors.