Pressure ulcers, also known as bedsores, are wounds that form when a person sits or lays in the same posture for an extended period of time. Continued pressure being applied to the same spot causes the skin to decay, possibly continuing into underlaying tissue if the wounds are not treated. A common and proven practice to prevent pressure ulcers from forming is to regularly change the posture of the patient, so that there is not too much pressure on any one part of the skin. Momo Medical is creating a sensor system to assist in preventing pressure ulcers. They already have a prototype using force-sensing resistor (FSR) and piezoelectric sensors to measure changes in posture of the patient. The prototype is able to detect if a patient has moved enough, whether on their own or by the nurses, to prevent pressure ulcers. The prototype works, but they need their system to be more reliable. The research in this thesis focuses on improving the piezoelectric sensors. Momo Medical uses the piezoelectric sensors to measure human bio-signals, mainly respiration and heart rate, through the mattress. Two different printed circuit boards (PCBs) were designed as test set-ups to be able to easily modify the amplifier to measure the piezoelectric sensors separately. Using these test set-ups two common piezoelectric sensors were compared, namely lead zirconate titanate (PZT) and polyvinylidene difluoride (PVDF) sensors. From this comparison it was concluded that the PVDF sensors consistently have a better signal-to-noise ratio (SNR), but that both the PZT and PVDF sensors were able to measure human bio-signals effectively. The PVDF sensors did showed even more promising results when using them in a different mechanical configuration. In the test set-up the amplifier was also changed to improve the read-out of the sensors. Multiple iterations on the amplifier design were tested. In the final design a non-inverting amplifier was chosen to decouple the amplification from the input impedance of the amplifier and a input impedance of 100MΩ was chosen. Because of the high input impedance in the final design the signal was dampened less and less amplification was needed, thus reducing noise.

An application-specific instruction set processor (ASIP) can provide for higher power and computationalefficiency compared to general-purpose processors. These attributes are essential for implantable medicaldevices which often run computationally intensive tasks on a strict power budget. This thesis compilesa collection of benchmarks by porting the existing benchmark suites ImpBench and CoreMark, and byimplementing a novel benchmark for artificial neural networks. Four architectures are selected in thecomparison; RISC, DSP, VLIW, and TTA. Implementations of these architectures are produced by theASIP Designer and OpenASIP toolsets. The benchmarks are simulated on these implementations andthe power consumption is measured on an FPGA. The thesis concludes that the implementations of theDSP and VLIW architectures do not deliver enough performance for their heavier use of resources, andrecommends a follow-up research by extending the TTA PeLoTTA and RISC-V Tzscale processors withapplication-specific instructions and running simulations for ASIC power and area numbers.