The ST1VAFE3BX chip combines highly accurate biopotential input with ST’s inertial sensing and AI core, which performs activity detection in the chip to ensure faster performance with lower power consumption.
“Wearable electronics is the critical enabling technology for the upsurge in individual health awareness and fitness. Today, everyone can have heart-rate monitoring, activity tracking, and geographical location on their wrist,” said Simone Ferri, APMS Group VP, MEMS Sub-Group General Manager at STMicroelectronics. “Our latest biosensor chip now raises the game in wearables, delivering motion and body-signal sensing in an ultra-compact form-factor with frugal power budget.”
The ST1VAFE3BX provides opportunities to extend wearable applications beyond the wrist to other locations on the body, such as intelligent patches for lifestyle or medical monitoring purposes.
The analogue front-end circuits for biopotential sensors are difficult to design and subject to unpredictable effects such as skin preparation and the position of electrodes attached to the body. The ST1VAFE3BX, however, provides a complete vertical analogue front end (vAFE) that simplifies the detection of different types of vital signs that can indicate physical or emotional state.
Manufacturers of wellness and healthcare devices will now be able to extend their product ranges to include functionality such as electrocardiography (ECG), electroencephalography (EEG), seismocardiography (SCG), and electroneurography (ENG). This can drive the emergence of new devices that are affordable, easy to use, and reliably indicate health status or physiological responses to events such as stress or excitement.
The ST1VAFE3BX, using ST’s established competencies in MEMS (microelectromechanical systems) devices, also integrates an accelerometer for inertial sensing. The accelerometer provides information about the wearer’s movement, which is synchronised with the biopotential sensing to help the application infer any link between measured signals and physical activity.
The ST1VAFE3BX also integrates ST’s machine-learning core (MLC) and finite state machine (FSM) that enable product designers to implement simple decision trees for neural processing on the chip.
These AI skills let the sensor handle functions such as activity detection autonomously, offloading the main host CPU to accelerate system responses and minimise power consumption. In this way, ST’s sensors let smart devices provide more sophisticated functions and operate for longer between battery charging, enhancing usability.
ST also provides software tools like MEMS Studio in the ST Edge AI Suite dedicated to helping designers unleash the maximum performance from the ST1VAFE3BX, including tools for configuring decision trees in the MLC.
The ST1VAFE3BX’s bio-detection signal channel comprises the vAFE with programmable gain and 12-bit ADC resolution. The maximum output data rate of 3200Hz is suitable for a wide variety of biopotential measurements to quantify heart, brain, and muscular activity.
The device is powered from a supply voltage in the range 1.62V to 3.6V and has typical operating current of just 50µA, which can be cut to just 2.2µA in power-saving mode.
The integrated low-noise accelerometer has programmable full-scale range from ±2g to ±16g.
In addition to the machine-learning core and programmable finite state machine, which can provide functionality such as activity detection, the ST1VAFE3BX implements advanced pedometer, step detector, and step counting functions.
