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Smart watches, rings, or accessories utilize optical sensors and accelerometers combined with powerful machine learning create exciting algorithms allowing parameters such as steps, calories, heart rate and its derivatives, blood oxygen, and sleep pattern to be predicted. The Quantified Self industry blossoms and wearable gadgets are now everywhere. We believe that wearable technology is still in its infancy and there are great potentials for the technology to disrupt existing clinical practices and aspire to diagnose or predict the onset of diseases that were once believed to be unpredictable. This presentation discusses pathways and activities needed to build wearable products beyond their current consumer-grade paving the way for wearable as a medical-grade device. Two specific examples will also be presented. The first example relates to how we use our wearables to discover a unique novel parameter that correlates to acute stress and how it is being utilized to improve the service of mental health counselling. The second example focuses on characterizing and correcting skin tone biased, an inherent problem associated with optical sensor, in pulse oximetry which has recently been reported for its racial and ethnic discrepancy.

Wearables and sensors are playing an increasingly important role in elderly care. Against the background of sociodemographic change and the lack of personnel, elderly care must be made more effective and efficient. IoT approaches can provide significant support in this regard. This presentation deals with the technology readiness level of existing solutions and outlines different use cases from the field.

As a concrete example, we will also present the digital care assistant we have developed using wearable sensors and low-cost printed electronics that can be integrated into any diaper, providing smart incontinence management, bed sore prevention, fall detection and resident localisation. We will discuss the impact this has had on residents wellbeing and carehome activities, and the challenges and lessons encountered on the way.

Wearables and sensors are playing an increasingly important role in elderly care. Against the background of sociodemographic change and the lack of personnel, elderly care must be made more effective and efficient. IoT approaches can provide significant support in this regard. This presentation deals with the technology readiness level of existing solutions and outlines different use cases from the field.

As a concrete example, we will also present the digital care assistant we have developed using wearable sensors and low-cost printed electronics that can be integrated into any diaper, providing smart incontinence management, bed sore prevention, fall detection and resident localisation. We will discuss the impact this has had on residents wellbeing and carehome activities, and the challenges and lessons encountered on the way.

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We are developing an innovative body-worn ultrasound device in a patch-based form-factor. Our device will allow for a revolution in patient monitoring, by allowing images of critical organ function to be collected, continuously and non-invasively by a body-worn device. Our first application will be targeted for the cardiac space, but our technology allows to address many other medical applications. In this talk we will highlight the technology and innovation behind our ultrasound patch

Wearable devices offer unique opportunities to acquire biosignals and provide short-latency biofeedback. This opportunity generated an ever-increasing interest in the last decade with numerous developments and wearable device market launches. Despite the great interest, the spread of wearable devices is still limited to a few categories like smartwatches and sports trackers, with limited products exploiting the enormous potential applications arising from brain (EEG), heart (ECG), muscles (EMG), and eyes (EOG) biosignals. Employing bio-potential signals in wearable devices would allow the user to get real-time health feedback or more seamless interaction with machines (i.e. brain-computer interface - BCI). However, the reliable acquisition of bio-potentials in wearable devices is very challenging as it requires high-quality sensing interfaces with the user's skin, coupled with miniaturized and high-performance hardware and software to meet key requirements for wearables, such as ease of use, unobtrusiveness, and high return of engagement, to mention a few. Only recently, only a few wearable devices were able to successfully satisfy these combined requirements, and the few available products mainly target BCI development or the meditation market. In this contribution, we report the development of a fully integrated in-ear sensor for brain signal detection meeting real needs of ease of use, non-stigmatizing form factor and high performance for long-term and multiple uses.
Two main features made possible the development of this fully integrated sensor for long-term use, namely the dry sensors and the newly developed acquisition system. The dry sensors used in this contribution are made of electrically conductive rubber material with silver/silver chloride coating on the areas in contact with the skin. These electrodes combine improved wear comfort (with respect to rigid metal or plastic dry electrodes) with low skin impedance and short equilibration time in bio-potential acquisition. Additionally, they can be used hundreds of times without a decrease in performance. The used production technology allows easy customization and it can be adapted to low as well as to serial volumes. In this contribution, we chose a custom brush-like design allowing easy ear canal penetration and comfort of use.

The acquisition system was designed to optimize the device’s size, energy consumption, and provide significant in-situ signal processing capabilities while allowing energy-efficient biosignal acquisition. At its core, it integrates an Ultra-Low-Power medical-grade 24-bit Analog-Front-End (AFE) engineered for biopotential acquisition. The AFE is coupled with a BLE-capable ARM Cortex-M4 microcontroller, enabling the whole platform to perform onboard processing of acquired data or wirelessly transmit the raw biosignal. The device also includes a Low-Power MEMS microphone and an inertial measurement unit. All components fit into a small (15x16mm) printed circuit board that can easily be placed on top of the ear, as a regular earbud would. When doing online processing, the device only employs 1.3 mW (including the energy required to transmit processing results), allowing more than a month of operation.

The strong synergy between the innovative electrodes and the novel acquisition device was demonstrated for a challenging auditory response (AR) use case. During tests, the device detected auditory stimuli from the EEG signals with a sensitivity and specificity >80%, only with a few training epochs. These results confirm the potential of the wearable system for complex diagnostic tasks, such as objective hearing threshold estimation, even in out-of-the-lab conditions.

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I will discuss how remote monitoring have the potential to transform the way we monitor and manage our health. Remote monitoring devices have already proven to be effective in providing continuous monitoring of vital signs such as heart rate, respiratory rate among others.

Pain is a significant global problem. For decades healthcare professionals have tried to find a way to measure pain. Now with the new wearable technology it is finally possible. To treat the pain, we need to be able to measure the pain, to continuously monitor a patient's pain levels and respond promptly with appropriate interventions. Intelligent wearable technology have the potential to revolutionize the pain management field by providing accurate and objective pain assessment data. This can help clinicians make more informed decisions on pain treatment, reducing the risk of overmedication and improving patient outcomes. Additionally, continuous monitoring of pain can provide valuable insights into the effectiveness of pain management strategies and help identify patients who may be at risk of developing chronic pain. I believe that the integration of intelligent wearable technology with skin patches into pain management protocols can significantly improve patient care and outcomes.
The key advantage of intelligent remote monitoring device is that they can be worn continuously without causing any discomfort to the user. This makes them ideal for patients who require long-term monitoring or those who need to be monitored remotely.

In my talk, I will also focus on the importance of signal processing and AI in ensuring that the captured data from the remote monitoring devices is reliable. Signal processing algorithms can help filter out noise and other unwanted signals, while AI can analyze the data to detect patterns and anomalies. This can help clinicians make more informed decisions and provide better care to their patients.

Finally, I will discuss the challenges that still need to be addressed in the development and implementation of intelligent remote monitoring devices. These include issues related to data privacy and security, regulatory approval, and cost-effectiveness. However, I am optimistic that these challenges can be overcome with continued innovation and collaboration between researchers, clinicians, and industry stakeholders.

In conclusion, remote monitoring have the potential to revolutionize the way we monitor and manage our health. They offer a non-invasive, comfortable, and continuous monitoring solution that can improve patient outcomes and reduce healthcare costs. I look forward to sharing my insights on this topic at your upcoming event.

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In this presentation, we will discuss the use of printed electronics in the development of customised electrode patches and smart textiles. Quad Industries has leveraged this technology to create innovative wearable healthcare products that offer several advantages over traditional approaches. Through the use of practical use cases, we will showcase the benefits of printed electronics, including enhanced comfort, flexibility, and functionality. Our presentation will demonstrate how this technology is revolutionizing the field of wearable healthcare, and we will provide insights into the potential for further innovation in this exciting area.

Discussing how healthcare-at-home remote diagnostics and clinical decision support utilizing A.I. / M.L.from wearables and e-textiles is now a prominent focus for all stakeholders in healthcare.
Shedding light on how textile-digital solutions are limited in the clinical and diagnostic services for dynamic data, particularly those utilizing A.I. / M.L.
Rethinking how textile + plus digital

Technical embroidery systems, due to their high precision, are applicable for the integration of functionality into textiles through textile sensors, actuators, electrodes and functional LED or RFID sequins. Even entire circuit boards (PCBs) can be automatically and reliably fixed and connected with conductive threads. Technical Embroidery systems provide solutions to two of the greatest challenges of the e-textiles industry by creating a reliable interface between the electronic components and the textile and enabling the automated mass production of smart and e-textiles.

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Neurotechnology research is making real the possibility of human brain and nervous system activity being measured and altered. Neurosensing can lead to better interfaces with technology, an increased understanding of the effectiveness of medication, and new insights into how the nervous system helps regulate physiology and biochemistry. Neuromodulation is enabling new approaches to therapies for rheumatoid arthritis, tinnitus, stroke, and Parkinson’s disease using wearable devices.

An overview of the variety of research at Stanford U. related to wearable eurotechnology will be presented, such as the following examples. Haptic wristbands stimulate nerves to create the perception of grasping an object in VR while leaving hands free. A functional Near-Infrared Spectroscopy (fNIRS) headband is in development for measuring blood flow changes in the brain that correspond to different mental states and may be used for biofeedback to reduce stress. Whereas electrocardiography (ECG) patches on the chest sense signals from the heart and detect arrhythmia, wearable sensors on the abdomen measure contractions of the stomach and gut to model the function of organs and help
clinicians diagnose digestive issues.

Electromyography (EMG) can be used with biofeedback to help individuals modify their walking gait to reduce long-term knee injury or improve athletic performance. EMG signals for muscles occur before the motion, which may lead to prediction of movement and increased responsiveness for exoskeletons.

Arrays of stretchable electrodes on the surface of the skin enable greater EMG precision than discrete electrodes when reading electrical signals. These e-skin arrays potentially lead to smoother control of robotics, feedback when training for delicate tasks, and more realistic interactions in VR.

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