Healthcare Monitoring Systems

Healthcare collects terabytes of dementia data but misses the signals that predict decline. As a neuropsychiatrist who builds technology, I've seen this measurement mismatch firsthand. Here's what we're missing: 1/ We track the wrong biomarkers ↳ Cognitive test scores capture late-stage changes ↳ Subtle functional changes precede test score drops by 18+ months ↳ Early warning signs hide in everyday activities, not office visits 2/ Our technology looks in the wrong places ↳ Most monitoring focuses on catastrophic events (falls, wandering) ↳ Gradual changes in sleep patterns signal decline months earlier ↳ Digital phenotyping can detect subtle rhythm disruptions 3/ Caregivers notice what our tools miss ↳ Changes in conversation patterns and word-finding ↳ Shifts in decision-making confidence go undocumented ↳ Technology rarely captures what caregivers instinctively observe 4/ The interaction gap drives misdiagnosis ↳ We evaluate symptoms in artificial clinical environments ↳ Most diagnostic errors happen from lack of real-world context ↳ Remote monitoring often disconnected from clinical workflow 5/ Precision requires integration ↳ Combining passive monitoring with caregiver observations ↳ Creating feedback loops between home and clinic ↳ Building technology that augments human observation, not replaces it The breakthrough insight? The most valuable dementia data comes from outside the healthcare system. Our best technology will bridge the gap between what clinicians measure and what patients and families experience. —----------------------------- ⁉️ What subtle changes have you noticed that standard assessments missed? ♻️ Share to help clinicians and technologists build better monitoring systems. 👉 Follow me (Reza Hosseini Ghomi, MD, MSE) for more at the intersection of brain science and technology.

Even before we’re aware of heart trouble or related health issues, our bodies give off warning signs in the form of vibrations. Technology to detect these signals has ranged from electrodes and patches to watches. Now, an innovative wall-mounted technology is capable of monitoring vital signs. Advanced TeleSensors Inc. developed the Cardi/o Monitor with an exclusive license from NASA’s Jet Propulsion Laboratory in Southern California. Over the course of five years, NASA engineers created a small, inexpensive, contactless device to measure vital signs, a challenging task partly because monitoring heart rate requires picking out motions of about one three-thousandth of an inch, which are easily swamped by other movement in the environment. By the late 1990s, hardware and computing technology could meet the challenge, and the NASA JPL team created a prototype the size of a thick textbook. It would emit a radio beam toward a stationary person, working similarly to a radar, and algorithms differentiated cardiac and respiratory activity from the “noise” of other movements. When Sajol Ghoshal, now CEO of Austin, Texas-based Advanced TeleSensors, participated in a demonstration of the prototype, he saw the potential for in-home monitoring. By then, developing an affordable device was possible due to the miniaturization of sensors and computing technology. The Cardi/o Monitor is 3 inches square and mounts to a ceiling or wall. It can detect vital signs from up to 10 feet. Multiple devices can be scattered throughout a house, with a smartphone app controlling settings and displaying all data on a single dashboard. The algorithms NASA developed detect heartbeat and respiration, and the company added heart rate variability detection that indicates stress and sleep apnea. If there’s an anomaly, such as a dramatic heart rate increase, an alert in the app calls attention to the situation. Up to six months of data is stored in a secure cloud, making it accessible to healthcare providers. This limits the need for regular in-person visits, which is particularly important for conditions such as infectious diseases, which can put medical professionals and other patients at risk. #JPL #NASA #Technology NASA uses radio frequency (RF) for a variety of tasks in space, including communications. The Europa Clipper RF panel — the box with the copper wiring near the top — will send data carried by radio waves through the spacecraft between the electronics and eight antennas. (NASA)

𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐇𝐞𝐚𝐫𝐭 𝐅𝐚𝐢𝐥𝐮𝐫𝐞 𝐂𝐚𝐫𝐞: 𝐓𝐡𝐞 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐟 𝐑𝐞𝐦𝐨𝐭𝐞 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 🏥❤️📊 As we continually strive to enhance patient outcomes and operational efficiency, remote monitoring for heart failure patients has emerged as a game-changer. Let's explore how this technology is transforming care delivery and improving lives. 𝐊𝐞𝐲 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐨𝐟 𝐑𝐞𝐦𝐨𝐭𝐞 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐢𝐧 𝐇𝐞𝐚𝐫𝐭 𝐅𝐚𝐢𝐥𝐮𝐫𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: 𝟏. 𝐑𝐞𝐝𝐮𝐜𝐞𝐝 𝐑𝐞𝐚𝐝𝐦𝐢𝐬𝐬𝐢𝐨𝐧𝐬 📉 Early detection of deterioration allows for timely interventions, significantly reducing unnecessary hospitalizations. 𝟐. 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞𝐝 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐀𝐥𝐥𝐨𝐜𝐚𝐭𝐢𝐨𝐧 📊 By prioritizing patients based on real-time data, we can better manage our time and resources. 𝟑. 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐌𝐞𝐝𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 💊 Remote data enables more precise titration of medications, enhancing treatment efficacy. 𝟒. 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐏𝐚𝐭𝐢𝐞𝐧𝐭 𝐄𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 🤝 Patients become active participants in their care, leading to better adherence and outcomes. 𝟓. 𝐃𝐚𝐭𝐚-𝐃𝐫𝐢𝐯𝐞𝐧 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐌𝐚𝐤𝐢𝐧𝐠 📈 Continuous monitoring provides a wealth of data for more informed clinical decisions. 𝟔. 𝐒𝐭𝐫𝐞𝐚𝐦𝐥𝐢𝐧𝐞𝐝 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 🔄 Automated alerts and data integration can significantly reduce administrative burden. 𝟕. 𝐄𝐱𝐭𝐞𝐧𝐝𝐞𝐝 𝐑𝐞𝐚𝐜𝐡 𝐨𝐟 𝐂𝐚𝐫𝐞 🌍 Particularly beneficial for rural or mobility-impaired patients, expanding our care beyond physical boundaries. Implementing remote monitoring isn't just about technology; it's about reimagining care delivery. It allows us to shift from reactive to proactive care models, potentially reducing costs while improving patient outcomes. 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐂𝐚𝐫𝐝𝐢𝐨𝐥𝐨𝐠𝐲: As we move towards value-based care, remote monitoring will play a crucial role in managing chronic conditions like heart failure more effectively and efficiently. 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐂𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧: - How has your organization implemented remote monitoring? - What challenges have you faced in adoption? - What outcomes have you observed? Let's discuss how we can leverage this technology to elevate our standard of care. Share your experiences and insights below. #HeartFailureManagement #RemotePatientMonitoring #HealthcareInnovation #CardiacCare #TeleHealth #ValueBasedCare #HealthTech #DigitalTransformation Interested in implementing or optimizing remote monitoring in your practice? Let's connect and explore strategies tailored to your organization's needs.

𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐇𝐞𝐚𝐥𝐭𝐡 𝐢𝐧 𝐑𝐞𝐦𝐨𝐭𝐞 𝐏𝐚𝐭𝐢𝐞𝐧𝐭 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 (𝐑𝐏𝐌) 𝐆𝐥𝐨𝐛𝐚𝐥 𝐒𝐭𝐚𝐫𝐭𝐮𝐩𝐬 𝐋𝐚𝐧𝐝𝐬𝐜𝐚𝐩𝐞 2.5𝐐 2024 The landscape of Remote Patient Monitoring (RPM) startups has evolved into a dynamic and rapidly growing segment within the broader digital health industry. As we approach the latter half of 2024, RPM has emerged as a crucial technology for managing chronic conditions, improving patient outcomes, and enhancing healthcare delivery efficiency. The global RPM market has seen significant advancements, driven by the integration of AI, wearable technology, and continuous health data analytics. Startups across the globe are leading the charge by offering innovative solutions that cater to various aspects of patient monitoring, from cardiac health to chronic disease management, maternal and fetal health, and even mental well-being. In the United States, companies like Accuhealth, AliveCor, and Athelas are at the forefront, providing real-time health data tracking and mobile ECG monitoring solutions. The integration of continuous glucose monitoring (CGM) with insulin management by Bigfoot Biomedical (Abbott) and the in-home health monitoring offered by Casana Care's Heart Seat highlight the diversity and depth of the RPM market. European startups are also making significant strides, with the UK’s Doccla and Huma offering digital health platforms for continuous patient management, while France’s Bioserenity and Implicity focus on chronic conditions and cardiac health, respectively. The incorporation of AI and machine learning is a common theme, enabling predictive analytics and personalized care, as seen with PhysIQ in the USA and IDOVEN in Spain. Moreover, the RPM landscape is not limited to traditional health metrics; companies like Starling Medical and Spire Health are pushing the boundaries by providing remote monitoring for urine diagnostics and respiratory health. The use of advanced technologies, such as micro-radar by Israel’s Neteera and contactless monitoring by India’s Tricog, further showcases the innovation driving this sector. As the RPM market continues to expand globally, the convergence of AI, digital health platforms, and wearable technology is set to revolutionize how healthcare is delivered, particularly in managing chronic diseases, post-treatment recovery, and even preventative care. This landscape report provides an in-depth look at the key players and emerging trends shaping the future of remote patient monitoring. #RemotePatientMonitoring #DigitalHealth #AIinHealthcare #Startups

In today’s connected world, mobile devices have become ubiquitous, including #digitalwearables that provide real-time information on physical activity, heart rate, sleep, oxygen saturation, and other clinical parameters. Digital #wearables are continuously evolving to monitor specific health concerns and present valuable data for disease monitoring. As the penetration of these devices increases, more health data can be integrated into clinical and research settings. New and innovative remote tools and sensors are changing how patients are cared for and what routine care can look like in the future. #remotedevices, sensors, diagnostic patches, and others are strengthening the existing systems to promote better patient monitoring and #diseaseprevention. These devices enable early detection of potential health issues, allowing for timely interventions before problems escalate. By tracking vital signs such as heart rate, blood pressure, and glucose levels in real-time, wearables provide continuous oversight and actionable insights for better health management. Remote sharing of critical data between key stakeholders across the care continuum can enable informed decision-making and timely responses to changes in patient conditions. Patients are also more engaged in their care, as wearables provide easy access to their #healthdata, encouraging active participation in managing their well-being. These technologies also enhance #medicationadherence through built-in reminders and alerts, ensuring patients stay on track with their prescriptions. Proactive, at-home management of chronic conditions through wearables helps reduce unnecessary hospital visits and streamline care. With their ability to promote independence and enhance overall well-being, wearables are a step toward smarter, more patient-centric healthcare delivery models.

The healthcare industry is undergoing a major transformation as medical device manufacturers expand beyond prescription-only products and bring advanced health monitoring tools directly to consumers. This shift, initially led by continuous glucose monitors (CGMs), is now spreading into broader areas of health, including cardiovascular monitoring and sleep diagnostics. Wearable and over-the-counter medical technologies are making it easier for people to track vital health metrics without requiring a doctor’s visit. Strategic partnerships between leading biosensing companies and wearable tech innovators are driving this change, integrating glucose, heart health, sleep, and stress data into seamless, user-friendly platforms. While this evolution offers greater accessibility and empowers individuals to take control of their health, it also raises concerns around medical oversight, data privacy, and the fine line between wellness tools and medical-grade care. As technology advances, regulatory bodies and healthcare professionals must find the right balance to ensure consumerized medical devices are both safe and effective. The question isn’t whether healthcare will continue shifting to consumer hands—it’s how quickly and how far this trend will go. Are we prepared for a future where real-time cardiac monitoring, sleep diagnostics, and even early disease detection are as common as a fitness tracker? #HealthTech #WearableTech #DigitalHealth #ConsumerHealth #HealthcareInnovation

The Internet of Medical Things (IoMT) refers to a connected network of medical devices, software applications, and healthcare systems that communicate over the internet. These devices collect, transmit, and analyze health data in real-time, improving patient care, reducing operational costs, and enhancing efficiency in healthcare systems. IoMT includes: Wearable devices, Connected medical equipment with remote monitoring, Smart hospital systems (e.g., real-time location tracking of assets and patients), Remote patient monitoring (RPM) systems, AI-driven diagnostics & analytics IoMT is transforming healthcare in the following ways: ✔️Remote Patient Monitoring & Home Healthcare ✔️Continuous monitoring of vital signs, glucose levels, ECG, and oxygen saturation using wearable IoMT devices. ✔️Reduces hospital admissions and improves chronic disease management ✔️Predictive Maintenance & Equipment Optimization ✔️IoMT-enabled medical devices detect failures before they occur, reducing downtime and improving hospital efficiency. ✔️Biomedical Engineers can use real-time diagnostics and remote troubleshooting for medical equipment. ✔️Smart Hospitals & Automation ✔️IoMT improves workflow automation by integrating RFID, AI, and robotics for tasks like asset tracking, smart inventory management, and automated patient check-ins. ✔️Reduces human errors and enhances hospital efficiency. ✔️AI-Powered Diagnostics & Decision Support ✔️AI and IoMT-enabled imaging devices can detect diseases earlier ✔️Physicians get real-time analytics to improve decision-making. ✔️Improved Patient Safety & Cybersecurity ✔️IoMT ensures continuous monitoring of critical patients, sending alerts for early intervention. IoMT is reshaping the role of Biomedical Engineers and Technicians, requiring them to develop new skills in addition to traditional medical equipment maintenance. 1. Knowledge of IoT & Network Infrastructure ◽️Understanding of wireless communication protocols ◽️Basics of networking ◽️Hands-on experience with real-time data transmission, cloud-based monitoring, and AI-driven analytics. 2. Cybersecurity & Data Protection ◽️Knowledge of medical device cybersecurity standards ◽️Implementing secure authentication, firewalls, and data encryption for medical devices. ◽️Understanding vulnerabilities of connected medical equipment and how to prevent cyberattacks. ◽️Predictive Maintenance & AI Integration ◽️Using AI-based predictive maintenance tools to detect early signs of equipment failure. ◽️Working with OEMs & third-party service providers for remote diagnostics. ➡️ Biomedical Engineers and Technicians need to upskill and adapt to remain relevant in the IoMT-driven future. Some key steps include: ✅ Certifications in IoT & cybersecurity ✅ Networking & cloud computing courses ✅ Hands-on experience with AI-driven diagnostics & predictive maintenance tools ✅ Continuous learning #Biomedical #Engineering 🤎

Telemedicine and home-based healthcare aren’t just trends, they’re the future of accessible, efficient patient care. But what's really going to take these services to the next level? It’s AI-driven tools that are transforming the way we deliver care, streamline operations, and improve patient outcomes.  So, how exactly is AI changing the game? Real-Time Monitoring: Always on the Pulse Imagine wearable devices that track vital signs in real-time, detecting heart rate irregularities, drops in blood oxygen, or sudden temperature spikes before they become major health risks. AI-powered tools can constantly analyze this data, flagging concerns early. This kind of proactive monitoring reduces unnecessary hospital visits and puts patients in control of their health. Remote Diagnosis: Your AI Assistant in Healthcare AI in telemedicine isn’t just about video calls, it’s about creating smart, supportive experiences. With AI algorithms, platforms can help analyze symptoms and even provide a preliminary diagnosis. Picture this: chatbots ask the right questions and gather data before a patient speaks to a doctor. Plus, AI-driven decision support tools are helping physicians make quicker, more accurate diagnoses and treatment recommendations. Personalized Care: No More One-Size-Fits-All When it comes to patient care, personalization is key. AI is using everything from medical history to genetics to create customized treatment plans. By spotting patterns in the data, AI helps doctors adjust treatments in real time, offering a home-based care experience that’s not just personalized but patient centered. Medication Reminders and Follow-Ups: Smarter Support Staying on track with medications and follow-ups can be tough, but AI tools can help. From personalized reminders for medications to gentle nudges for follow-up appointments, these tools keep patients engaged and ensure they stick to their care plans. The best part? Continuous feedback from these tools allows healthcare providers to stay on top of patient progress. Think AI: Taking Telemedicine to the Next Level At ThinkAI, we’re making all this a reality. Our AI-powered Healthcare Analytics tools integrate real-time patient data, enabling seamless remote monitoring and proactive care. Plus, we make sure your telehealth platforms integrate smoothly with existing systems, like EHRs, so your team gets a unified, hassle-free experience. Think AI isn’t just about providing tools, it’s about crafting smart strategies. We help healthcare organizations adopt AI for diagnostics and personalized care, enhancing their telemedicine services without disrupting daily operations. Ready to take your telemedicine services from basic calls to next-gen, data-driven virtual care? Let’s innovate together! #Telemedicine #HealthcareInnovation #AIinHealthcare #DigitalHealth

Today was my first day as Biomedical Engineer in Hospital I visited pediatric ICU ( children ICU ) I saw a most common equipment there Have you ever heard of a Patient Monitoring System? Maybe you've heard of it but do you know why it's so important? Imagine a monitor showing your heart rate, SpO2, and other vital signs like this: - Heart Rate: 78 bpm - SpO2: 98% - Blood Pressure: 120/80 mmHg But how my coding skills can modify this ? Well I will choose machine learning algorithm " Random forest" - The system will collect vital sign data from patients. - The data will be cleaned and processed to remove any errors or inconsistencies. -Relevant features will be extracted from the data, such as heart rate variability and blood pressure trends. - The algorithm will be trained on the processed data to learn patterns and relationships. - Then this trained model will be deployed in PMS to predict problems - If the system detects any potential problems, like abnormal ECG , it will alert hospital staff to take action. By using Machine learning, we can improve patient outcomes, reduce hospital stays, and enhance healthcare efficiency. ☘️ Share your ideas how machine learning can modify this biomedical equipment?