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Cognitive impairment has become epidemic in older adult population. The recent advent of tiny wearable and ambient devices, a.k.a Internet of Things (IoT) provides ample platforms for continuous functional and cognitive health assessment of older adults. In this paper, we design, implement and evaluate AutoCogniSys, a context-aware automated cognitive health assessment system, combining the sensing powers of wearable physiological (Electrodermal Activity, Photoplethysmography) and physical (Accelerometer, Object) sensors in conjunction with ambient sensors. We design appropriate signal processing and machine learning techniques, and develop an automatic cognitive health assessment system in a natural older adults living environment. We validate our approaches using two datasets: (i) a naturalistic sensor data streams related to Activities of Daily Living and mental arousal of 22 older adults recruited in a retirement community center, individually living in their own apartments using a customized inexpensive IoT system (IRB #HP-00064387) and (ii) a publicly available dataset for emotion detection. The performance of AutoCogniSys attests max. 93\% of accuracy in assessing cognitive health of older adults.

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Systems and methods for detecting biometrics using microwave radar sensor modules are disclosed. Integrated microwave sensor modules can include a transmitter unit configured to generate at least one continuous wave transmit signal based upon at least one frequency control signal, a receiver unit configured to utilize a cancellation path to cancel contributions to a return signal based upon at least one cancellation path control signal, and a microcontroller unit that includes a processor, a memory containing a microcontroller application, where the microcontroller application configures the processor to generate at least one frequency control signal to generate least one CW transmit signal having a plurality of frequencies, generate at least one cancellation path control signal to automatically adjust the cancellation path in real time, receive at least one demodulated signal, digitize the at least one demodulated signal, and update the at least one frequency control and cancellation path control signals.