MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541123869 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy College Of Engineering And Technology; Malla Reddy Engineering College For Women; Malla Reddy University; and Malla Reddy Vishwavidyapeeth, Medchal-Malkajgiri, Telangana, on Dec. 9, 2025, for 'low power data acquisition system for biomedical monitoring.'
Inventor(s) include Dr. G. Hema; M. Sai Krishna Murthy; Mr. Kallubhavi Obulesh; Dr. Pujari Neha; Dr. K Vidhyapriyadharshini; and Dr. Katam Naga Lakshman.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The present invention reveals an advanced Low Power Data Acquisition (DAQ) System designed particularly for the long term biomedical monitoring applications. In the fast-changing field of Internet of Medical Things (IoMT) and wearable health technology, an important bottleneck is the low-energy capacity of portable sources compared with the high power requirement of a continuous physiologic signal processing. Conventional data acquisition architectures usually employ data acquisition techniques that have fixed sampling rates and are based on the Nyquist criterion which requires the acquisition and processing of redundant data points during periods of low physiological activity, resulting in rapid battery depletion and frequent recharging or battery replacement. The invention solves these significant drawbacks by presenting an intelligent and event-based architecture for modulating power consumption depending on real-time characteristics of the applied input biological signals. The system contains a very efficient, multi-stage Analog Front End (AFE) coupled with a new adaptive sampling controller. Unlike traditional systems which continuously digitize analog signals with the maximum resolution, the proposed invention makes use of an activity detection circuit which monitors the analog signal slope and amplitude in the pre-processing stage. When the physiological signal, such as Electrocardiogram (ECG) or Electroencephalogram (EEG), is free or below a clinically relevant threshold value, the high rate Analog-to-Digital Converter (ADC) and main processing unit are put in a deep sleep state. The system is only woken up to the power hungry components when a significant deviation or specific feature is detected, meaning that energy is only expended when there is valuable information present. Furthermore, the invention provides a hierarchical power management unit for optimizing the transmission of data to external receivers. Wireless Transmission is in biomedical devices often the single largest consumer of energy. To reduce this, the current system consists of an on-chip compression engine, which uses algorithms for data compression, which are based on lossless data compression for biological waveforms. By shortening the packet size before packet transmission, and using the burst mode of communication protocol, the duty cycle of the radio frequency (RF) transceiver is reduced. This way, the lifespan of the device is extended to a large degree, the device can be used for implantable applications where it is surgical and risky to replace the battery. Finally, the architecture is made agnostic to the type of biomedical sensor that is used to provide a versatile platform for various health monitoring needs. Whether used for a patch-based heart monitor, a glucose sensing implant, or a wearable pulse oximeter, the system self-calibrates the noise floor and the trigger levels. This flexibility in combination with the extreme power efficiency thanks to the synergy between adaptive sampling and smart data transmission represents a paradigm shift in the way health data in the longitudinal domain is being captured: uninterrupted periods of weeks and months of monitoring are possible rather than days."
Disclaimer: Curated by HT Syndication.
