Microneedle Waveguides for Wearable Deep-Tissue Sensing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing monitoring devices struggle to penetrate deep tissues for accurate biological signal collection due to attenuation and scattering by skin layers, while implantable devices pose infection risks.
Innovation Solution
A wearable apparatus with biocompatible microneedles configured as waveguides for sensing wave signals, enabling deep tissue data collection and wireless communication, using light or ultrasonic signals, with a control module for signal processing and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical-based wearable devices are positioned above the skin surface, then the devices can be non-invasive and wearable, but they lack sufficient ability to penetrate through cutaneous and subcutaneous layers to collect adequately interpretable data from deeper regions
Solution Approach 1:
The patent introduces microneedles as intermediary structures that penetrate the skin barrier to reach deep tissues. These microneedles serve as conduits for delivering optical sensors and waveguides directly to the target tissue, bypassing the attenuating and scattering effects of the skin layers. The microneedles act as a mediator between the external device and the deep tissue, enabling accurate sensing without requiring the entire optical path to traverse the skin.
Solution Approach 2:
The patent segments the sensing system into multiple functional components: external wearable device, microneedle array, and deep tissue sensing region. The microneedles are individually positioned to reach specific deep tissue locations, allowing the system to divide the complex task of penetrating skin and sensing deep tissue into separate manageable stages. This segmentation enables precise targeting of deep tissues while keeping the external device simple and wearable.
2Measurement precision
If implantable devices are inserted at depth through invasive surgical procedures to bypass skin barriers, then deep tissue sensing can be achieved, but there is a cost of significant and/or non-negligible infection and inflammation risk
Solution Approach 1:
The patent extracts the sensing function from the skin surface and places it at the deep tissue interface through microneedles. By taking out the sensing components and positioning them directly at the deep tissue location via the microneedle array, the system achieves deep tissue sensing without requiring extensive invasive surgery. The microneedles are minimally invasive compared to traditional surgical implantation, reducing the risk of infection and inflammation while still enabling access to deep tissues.
Solution Approach 2:
The patent transitions from surface-level sensing to three-dimensional deep tissue sensing by inserting microneedles at angles that penetrate through the skin barrier. This dimensional change allows the sensing elements to be positioned at deep tissue depths while maintaining a minimal invasive entry point. The angled insertion and varying lengths of microneedles create a three-dimensional sensing architecture that reaches deep tissues without requiring extensive surgical exposure, thereby reducing infection risk.
3Measurement precision
If microneedles are used as waveguides to enhance penetration of sensing wave signals, then deep tissue data collection is enabled, but the device complexity increases
Solution Approach 1:
The patent designs the microneedles to serve multiple functions simultaneously: they act as mechanical penetrators to breach the skin barrier, as structural supports to position sensing elements, as optical waveguides to transmit signals to deep tissues, and as anchoring structures to secure the device. By making the microneedles multi-functional, the system reduces the need for separate components for each function, thereby managing device complexity while enabling deep tissue data collection.
Solution Approach 2:
The patent merges the functions of the microneedle array with the optical sensing system. The microneedles are integrated with waveguides and sensing elements into a unified assembly that can be deployed as a single minimally invasive unit. This merging of components simplifies the overall device architecture compared to having separate systems for skin penetration, signal transmission, and data collection. The integrated design allows the microneedle array to function as both the delivery mechanism and the sensing platform.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables reliable and accurate deep tissue sensing without invasive procedures, providing continuous monitoring of physiological parameters like tissue oximetry and heart pulsation.
Implementation Method 1
the plurality of microneedles are configured to waveguide the wave signals into a deep tissue of the subject
Implementation Method 2
these layers are generally attenuating, light-scattering, and wave-absorbing
Implementation Method 3
optical-based wearable devices positioned above and interfacing with a skin surface may lack sufficient ability to penetrate through cutaneous and subcutaneous layers
Implementation Method 4
one or more waveform generators configured to emit wave signals
Implementation Method 5
one or more waveform generators configured to emit wave signals
Implementation Method 6
detection of reflections thereof
Data Source
AI summary
Various example of the present disclosure provide sensing apparatuses configured for wearable and wireless use for deep tissue physiological monitoring. The sensing apparatuses may be embodied by a thin flexible patch configured to conform with a skin surface of a subject. A sensing apparatus may include a plurality of microneedles oriented to extend towards and penetrate into the subject to a shallow depth. The microneedles may be configured as waveguides for a given sensing modality (e.g., light, ultrasound), such that sensing wave signals propagate to deep tissues. For the sensing, the sensing apparatus includes waveform generators (e.g., light-emitted diodes) and waveform detectors (e.g., photodiodes). Machine learning models may be used to process and denoise sampled data from the waveform detectors and to generate accurate and reliable physiological measurements, including heart rate, respiratory rate, pulse intensity, respiratory intensity, blood oximetry, tissue oximetry, blood flow rate, and/or the like.