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The mathematical properties of high-dimensional spaces seem remarkably suited for describing behaviors produces by brains. Brain-inspired hyperdimensional computing (HDC) explores the emulation of cognition by computing with hypervectors as an alternative to computing with numbers. Hypervectors are high-dimensional, holographic, and (pseudo)random with independent and identically distributed (i.i...
The stringent power constraints of complex microcontroller based devices (e.g. smart sensors for the IoT) represent an obstacle to the introduction of sophisticated functionality. Programmable accelerators would be extremely beneficial to provide the flexibility and energy efficiency required by fast-evolving IoT applications; however, the integration complexity and sub-10mW power budgets have been...
Pattern recognition and classification algorithms are widely studied in natural gesture interfaces for upper limb prostheses. Robustness and accuracy of control systems are key challenge in such applications. To improve the classification performance, the conventional approach builds on classifier parameters tuning and/or feature extraction techniques. In this paper, we propose a complementary approach...
Patient monitoring systems are becoming increasingly important in accurately diagnosing and treating growing worldwide chronic conditions especially the obesity epidemic. The ubiquitous nature of wearable sensors, such as the readily available embedded accelerometers in smart phones, provides physicians with an opportunity to remotely monitor their patient's daily activity. There have been several...
Daily life activities such as working and shopping may cause people to carry overloaded bags, frequently borne in an incorrect way (e.g. only on one shoulder, asymmetrically worn). When these activities alter the gait, back pain incidents can occur. Critical conditions can be monitored taking advantage from a wearable assistant, extracting contextual information by on-body acceleration signals. By...
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