Electronic sensor systems, most often designed in CMOS technology, are key components of biomedical wearable devices, which are part of the emerging mobile health paradigm. These devices sense physiological signals from the patient and process the acquired data to provide clinical information. Besides the potential medical and cost benefits of wearable systems, the environmental sustainability of these devices is a critical factor given their expected widespread deployment. This thesis aims at optimizing mixed-signal sensor systems for low power consumption to limit the need for battery capacity and the associated environmental impacts. In addition, we pursue low-complexity yet programmable sensor systems to limit the environmental footprint of their production and the risk of obsolescence. In the first part, we demonstrate the circuit-level design of a low-power signal acquisition and processing system on a custom ultra-low-power microcontroller in the use case of electrocardiogram arrhythmia classification. System-level optimization of this cardiac monitoring system is performed in the second part, to further minimize the total power consumption while maintaining a high classification accuracy. Finally, we take a step back at the application level and show that, in addition to the direct environmental impacts of wearable devices related to their life cycle, more attention should be devoted to their indirect environmental impacts such as care optimization, induced medicalization, or structural rebound effects.
Dekimpe, R. (2022). Cross-layer and cross-domain power optimization towards sustainable biomedical CMOS sensor systems. https://hdl.handle.net/2078.5/27883