Health Technologies: diagnostics

Showing posts with label diagnostics. Show all posts

Thursday, January 11, 2024

Smart Homes Redefined

The concept of a smart home has evolved significantly, with technologies now focusing on health monitoring. The integration of advanced sensors and devices into our living spaces promises not only convenience but also proactive health management.

While sensors placed throughout the home can detect air and water contaminants, allergens, and pollutants, high-resolution cameras and microphones and other non-contact measurement devices could allow health monitoring and remote consultations with healthcare professionals.

Smart mirrors in bathrooms should transcend mere reflective surfaces. Enhanced with advanced computer vision capabilities, they could assess skin conditions, identify changes in appearance, and offer personalized health and beauty recommendations. They could also analyze the eyes for early signs of various health conditions, extending far beyond mere glaucoma and cataract detection. The eyes can unveil valuable information about cholesterol levels, liver conditions, and diabetes. Eye monitoring technology is a testament to the saying, "The eye is the window to the soul," extending its truth to health monitoring.

Ambient sensors equipped with radar technology in living rooms and bedrooms can continuously monitor vital signs like pulse rates. This non-intrusive monitoring could provide a seamless health tracking experience for residents.

Recent advancements include the use of mmWave radar sensors for continuous monitoring of human activity. Recently built system, utilizing an NVIDIA Jetson Nano board for real-time processing and a Texas Instruments Millimeter-Wave Radar Sensor, offers a non-intrusive and privacy-respecting way to monitor activities like sitting, walking, standing, and even detecting falls. This radar technology poses a challenge due to the high-dimensional point cloud data it generates. The PointNet neural network is developed to process this data efficiently, preserving spatial relationships and offering accurate activity classification.

The traditional method of measuring SpO2 involves contact sensors, which can be inconvenient for prolonged use. New techniques for contactless SpO2 measurement using different light wavelengths in video images are being developed. This approach promises a more comfortable and accessible way to monitor oxygen saturation levels, especially crucial in the wake of health crises like COVID-19.

The COVID-19 pandemic has underscored the importance of non-intrusive health monitoring, especially for elderly individuals. The development of a Multi-scaled Long Short Term Memory (Ms-LSTM) model, as part of a smart toilet system, represents a significant step in this direction. This model enables effective home-based health diagnostics through urine analysis, leveraging the IoT-Fog-Cloud paradigm. It's a particularly vital tool for early detection of potential viral infections, including COVID-19, in the elderly. The Ms-LSTM model integrates a four-layered architecture including data acquisition, fog layer (processing and analyzing the data locally) , cloud (for deeper analysis) and interface layer. The proposed system offers a non-invasive, efficient method for early disease detection and preventive health.

The integration of health monitoring technologies into smart homes is transforming how we approach personal health. From environmental sensors to advanced radar and neural networks, these innovations promise a future where health management is seamlessly woven into our daily lives. As technology continues to advance, we can expect even more sophisticated health monitoring solutions to emerge, making proactive health care a tangible reality in the comfort of our homes.

REFERENCES

Alhazmi AK, Alanazi MA, Alshehry AH, Alshahry SM, Jaszek J, Djukic C, Brown A, Jackson K, Chodavarapu VP. Intelligent Millimeter-Wave System for Human Activity Monitoring for Telemedicine. Sensors (Basel). 2024 Jan 2;24(1):268. doi: 10.3390/s24010268. PMID: 38203130.

Sasaki S, Sugita N, Terai T, Yoshizawa M. Non-Contact Measurement of Blood Oxygen Saturation Using Facial Video Without Reference Values. IEEE J Transl Eng Health Med. 2023 Sep 25;12:76-83. doi: 10.1109/JTEHM.2023.3318643. PMID: 38088997; PMCID: PMC10712673.

Kumar D, Sood SK, Rawat KS. Empowering elderly care with intelligent IoT-Driven smart toilets for home-based infectious health monitoring. Artif Intell Med. 2023 Oct;144:102666. doi: 10.1016/j.artmed.2023.102666. Epub 2023 Sep 20. PMID: 37783534.

Fatima H, Imran MA, Taha A, Mohjazi L. Internet of Mirrors for Connected Healthcare and Beauty: A Prospective Vision. arXiv preprint arXiv:2311.14734. 2023 Nov 21.

Saturday, August 17, 2013

Building a 23rd Century Tricorder in the 21st

The $10 million Qualcomm Tricorder X Prize and $2.25 million Nokia Sensing XCHALLENGES are trying to identify the best portable technologies for diagnosing disease - as easily as Dr. McCoy's tricorder of the 23rd Century could. What scientific knowledge could help us to develop it in this age? Detecting metabolites, sensing DNA, imaging the nanoworld of the human body or interaction between matter and energy?

Medical diagnostics was always a multi-modal procedure. Even ancient physicians used optical sensing (observation), audio (auscitation) and olfaction along with interrogation and pattern recognition techniques. "The best diagnostic test" was always different for any given situation.

And the so much sought after tricorder can't be only about a single technological innovation or the right combination of existing measurement technologies, it is also about putting all the pieces together in a system that's smaller, lighter, cheaper, faster, better.

21st-century innovation is proving to be even more prolific than that of the 20th. Too many ideas, too few financially-supported ventures pursuing some of them. Yet, these 12 finalists of Nokia Sensing Challenge give an idea of what technologies are among the most popular. Here's the list:

Diagnostic Device	Sensing platform	Examples of diagnostic applications
Apollo	Optical - Spectrophotometer	Noninvasive glucose monitoring
Holomic	Optical - lens-free microscope	Blood analysis, HIV monitoring
i-calQ	Optical	Blood and saliva analysis, Ebola monitoring
InSilixa	Electrical	Genetic diagnostics
MoboSens	Electrical	Water pollution monitoring
Gene- RADAR	Biochemical	Virus detection
Programmable-Bio-Nan-Chip	Flluorescence, Immunoassays	Heart disease
QUASAR	Electromagnetic, ECG	Heart disease
Silicon BioDevices	Immunoassays	Blood analysis
ABUS-urodynamics	Ultrasound	Disorders of urinary system
Elfi-Tech	Occlusion Spectroscopy	Noninvasive cardiac monitoring
Owlstone	Chemical - Field Asymmetric Ion Mobility Spectrometer	Noninvasive glucose monitoring

REFERENCES

Waters H (2011). New $10 million X Prize launched for tricorder-style medical device. Nature medicine, 17 (7) PMID: 21738131

Wednesday, November 4, 2009

Thoughts on the Future of Dx

Workflow, procedures and organization of diagnostic laboratories have changed little since the end of the 19th century. Technology improved quality and safety, lead to higher throughput and allowed private electronic access to patients' lab test results - at least partially, but other than that not much has changed.

The introduction of first generation transcriptome technologies in the mid 1990s

(Schenaet al., 1995; DeRisi et al., 1996) has led to a phenomenal abilityto simultaneously measure thousands of genes, create molecular profiles of cancers, all other diseases and conditions.

Proteomics - coined a couple of years later (James, 1997) - was accepted as an even more promising technique for effective diagnostics of diseases. Figure on the left, however, demonstrates that it too faces many challenges from discovery of biomarkers to their verification and approval. After more than a decade (Oliver et al., 1998), metabolomics has been accepted as - at least - an equally promising technique, but it still lagging behin genomics and proteomics.

All these techniques will have significant impact on the business model of diagnostics. Multiplexing (measuring multiple biomarkers at once) is obviously much more cost-effective. Diagnostics industry is historically very resistant to disruptive technological change, but potential cost advantages should outweigh this, leading to novel business models in health management.

A change will also come from the growing near patient testing (NPT) sector. NPT is already finding a role in wellness monitoring. Existing self tests - such as cholesterol kits - may not be very accurate, but with the advent of inexpensive multiplexing assays this will be overcome. Even when blood testing is done by trained professionals in a lab, there can be significant variability in test results. Same applies to blood pressure measurements - you may need to do three measurements per day for five days in order to get a decent baseline. This only justifies the need to have inexpensive tests that can be done more often.

But lets go back to metabolomics and its potential to provide noninvasive inexpensive diagnostics. Are there any clinical trials attempting to translate it into clinical practice?
Here are our favorite ones:

CANCER
NCT00757952: Diagnosing ovarian cancer in exhaled breath. (Pine Street Foundation & University of Maine)
NCT00898209: Diagnosing Lung cancer in exhaled breath. (Vanderbilt-Ingram Cancer Center)
NCT00898209: Exhaled breath analyzed for lung cancer. (Vanderbilt-Ingram Cancer Center)
NCT00639067: Breath test for early detection of lung cancer (Menssana Research)
NCT00873366: Breath tests to access effectiveness of breast cancer treatment (Mayo Clinic and National Cancer Institute (NCI))

OTHER
NCT00330603: Metabolomic breath analysis to predict treatment for chronic cough (University of Virginia)
NCT00632307: Breath analysis to diagnose COPD; lung cancer; airway infection; interstitial lung disease, sleep apnea; pulmonary disorders with pleural infusions; sarcoidosis (Lung Clinic Hemer, Germany)
NCT00294489: Breath analysis to diagnose Hepatitis C (Hadassah Medical Organization, Jerusalem, Israel)

References
Schena M, Shalon D, Davis RW, Brown PO 1995 Quantitative monitoring of gene expression patterns with complementary DNA microarray. Science 270 : 467 –470[Abstract/Free Full Text]

DeRisi J, Penland L, Brown PO, Bittner ML, Meltzer PS, Ray M, Chen Y, Su YA 1996 Use of a cDNA microarray to analyze gene expression patterns in human cancer. Nat Genet 14 : 457 –460[CrossRef][Medline]

James P 1997 Protein identification in the post-genome era: the rapid rise of proteomics.". Quarterly reviews of biophysics 30 (4): 279–331. doi:10.1017/S0033583597003399. PMID 9634650.

Oliver SG, Winson MK, Kell DB, Baganz F. 1998. Systematic functional analysis of the yeast genome. Trends in Biotechnology 16: 373-378.

Aurametrix is conducting research to develop next-generation diagnostics to help you evaluate your personal health risks and benefits. Better tools for a healthier world.