Erratum: Survey of Conductive Polymers for the Fabrication of Conformation Switching Nucleic Acid-Based Electrochemical Biosensors.

[This corrects the article DOI: 10.1021/acsapm.3c02206.].

Multiplexed Chemical Sensing CMOS Imager.

A miniaturized and multiplexed chemical sensing technology is urgently needed to empower mobile devices and robots for various new applications such as mobile health and Internet of Things. Here, we show that a complementary metal-oxide-semiconductor (CMOS) imager can be turned into a multiplexed colorimetric sensing chip by coating micron-scale sensing spots on the CMOS imager surface. Each sensing spot contains nanocomposites of colorimetric sensing probes and silica nanoparticles that enhance sensing signals by several orders of magnitude. The sensitivity is spot-size-invariant, and high-performance gas sensing can be achieved on sensing spots as small as ∼10 µm. This great scalability combined with millions of pixels of a CMOS imager offers a promising platform for highly integrated chemical sensors. To prove its compatibility with mobile electronics, we have built a smartphone accessory based on this chemical CMOS sensor and demonstrated that personal health management can be achieved through the detection of gaseous biomarkers and pollutants. We anticipate that this new platform will pave the way for the widespread application of chemical sensing in mobile electronics and wearable devices.

Mitigation of Data Packet Loss in Bluetooth Low Energy-Based Wearable Healthcare Ecosystem.

Bluetooth Low Energy (BLE) plays a critical role in wireless data transmission in wearable technologies. The previous work in this field has mostly focused on optimizing the transmission throughput and power consumption. However, not much work has been reported on a systematic evaluation of the data packet loss of BLE in the wearable healthcare ecosystem, which is essential for reliable and secure data transmission. Considering that diverse wearable devices are used as peripherals and off-the-shelf smartphones (Android, iPhone) or Raspberry Pi with various chipsets and operating systems (OS) as hubs in the wearable ecosystem, there is an urgent need to understand the factors that influence data loss in BLE and develop a mitigation solution to address the data loss issue. In this work, we have systematically evaluated packet losses in Android and iOS based wearable ecosystems and proposed a reduced transmission frequency and data bundling strategy along with queue-based packet transmission protocol to mitigate data packet loss in BLE. The proposed protocol provides flexibility to the peripheral device to work with the host either in real-time mode for timely data transmission or offline mode for accumulated data transmission when there is a request from the host. The test results show that lowered transmission frequency and data bundling reduce the packet losses to less than 1%. The queue-based packet transmission protocol eliminates any remaining packet loss by using re-request routines. The data loss mitigation protocol developed in this research can be widely applied to the BLE-based wearable ecosystem for various applications, such as body sensor networks (BSN), the Internet of Things (IoT), and smart homes.

A Microdroplet-Based Colorimetric Sensing Platform on a CMOS Imager Chip.

Interest in mobile chemical sensors is on the rise, but significant challenges have restricted widespread adoption into commercial devices. To be useful these sensors need to have a predictable response, easy calibration, and be integrable with existing technology, preferably fitting on a single chip. With respect to integration, the CMOS imager makes an attractive template for an optoelectronic sensing platform. Demand for smartphones with cameras has driven down the price and size of CMOS imagers over the past decade. The low cost and accessibility of these powerful tools motivated us to print chemical sensing elements directly on the surface of the photodiode array. These printed colorimetric microdroplets are composed of a nonvolatile solvent so they remain in a uniform and homogeneous solution phase, an ideal medium for chemical interactions and optical measurements. By imaging microdroplets on the CMOS imager surface we eliminated the need for lenses, dramatically scaling down the size of the sensing platform to a single chip. We believe the technique is generalizable to many colorimetric formulations, and as an example we detected gaseous ammonia with Cu(II). Limits of detection as low as 27 ppb and sensor-to-sensor variation of less than 10% across multiple printed arrays demonstrated the high sensitivity and repeatability of this approach. Sensors generated this way could share a single calibration, greatly reducing the complexity of incorporating chemical sensors into mobile devices. Additional testing showed the sensor can be reused and has good selectivity; sensitivity and dynamic range can be tuned by controlling droplet size.

Developing a Low-Cost Wearable Personal Exposure Monitor for Studying Respiratory Diseases Using Metal-Oxide Sensors.

Global industrialization and urbanization have led to increased levels of air pollution. Those with respiratory diseases, such as asthma, are at the highest risk for adverse health effects and reduced quality of life. Studying the relationship between pollutants and symptoms is usually achieved with data from government air quality monitoring stations, but these fail to report the spatial and temporal resolution required to track a person's true exposure, especially when the majority of their time is spent indoors. We develop and build eight wrist-worn wearable devices, weighing only 64 g, to measure known asthma symptom triggers: ozone, total volatile organic compounds, temperature, humidity, and activity level. The devices use commercial off-the-shelf components, costing under $150 each to build. This report focuses on the design, calibration, and testing of the devices. Emphasis is placed on the calibration of a metal-oxide-semiconductor gas sensor for detecting ozone, which is a difficult task because of the large variations in ambient temperature and humidity found when using a wearable device. Examples of testing the devices in four real environments are also discussed: 11 days inside a well-ventilated laboratory, ten days outdoors during the summer, alternating the devices between indoor and outdoor environments to examine their response to quickly changing environments, and a field test where scripted activities are performed for a full day. The work demonstrates a wearable device for environmental health studies and addresses the challenges of existing sensors for real-world applications.