Chemical Vapor Deposition
Chemical vapor deposition is a nascent, single-step processing method for forming electronic polymer films on unconventional substrates and is increasingly important for creating flexible and wearable electronics. A suite of vapor-phase polymerization reactions performed inside reduced-pressure hot wall reactors, collectively termed CVD, are the enabling methods we use to build novel devices.
CVD can be interpreted as a solvent-free synthetic technique, where multiple reagents converge in the vapor phase to effect a polymerization reaction. In CVD, polymer films are formed directly on the substrate of interest as vapors of a chemical agent and precursor (or monomer) are introduced into an evacuated reactor chamber simultaneously. This method allows for conformal coating of rough surfaces, with features resolvable down to 100-200 nm. The modularity of CVD ensures that careful monomer choice will lead to the in situ film growth of a host of functional polymers displaying varied properties.
Dr. Andrew's Research
2022
Andrew, Trisha L; Rostaminia, Soha; Homayounfar, S Zohreh; Ganesan, Deepak
Perspective—Longitudinal Sleep Monitoring for All: Payoffs, Challenges and Outlook Journal Article
In: ECS Sensors Plus, vol. 1, no. 1, pp. 011602, 2022.
@article{andrew2022perspective,
title = {Perspective—Longitudinal Sleep Monitoring for All: Payoffs, Challenges and Outlook},
author = {Trisha L Andrew and Soha Rostaminia and S Zohreh Homayounfar and Deepak Ganesan},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {ECS Sensors Plus},
volume = {1},
number = {1},
pages = {011602},
publisher = {IOP Publishing},
abstract = {Longitudinal tracking of sleep metrics is important for detecting and managing various diseases, spanning cardiorespiratory disorders to dementia. However, at present, sleep monitoring primarily occurs in specialized medical facilities that are not conducive to long-term studies. In-home solutions either compromise user comfort or signal accuracy in tracking sleep variables and have not yet provided reliable longitudinal data. Here, we survey the current state of sleep trackers and highlight key shortcomings to provide guiding principles for improved sensor system design. We believe that human-centered design of multimodal, low-form-factor, comfortable sensing systems is needed for this increasingly-important area of human health monitoring.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Longitudinal tracking of sleep metrics is important for detecting and managing various diseases, spanning cardiorespiratory disorders to dementia. However, at present, sleep monitoring primarily occurs in specialized medical facilities that are not conducive to long-term studies. In-home solutions either compromise user comfort or signal accuracy in tracking sleep variables and have not yet provided reliable longitudinal data. Here, we survey the current state of sleep trackers and highlight key shortcomings to provide guiding principles for improved sensor system design. We believe that human-centered design of multimodal, low-form-factor, comfortable sensing systems is needed for this increasingly-important area of human health monitoring.
Kiaghadi, Ali; Huang, Jin; Homayounfar, Seyedeh Zohreh; Andrew, Trisha; Ganesan, Deepak
FabToys: plush toys with large arrays of fabric-based pressure sensors to enable fine-grained interaction detection Inproceedings
In: Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services, pp. 1–13, 2022.
@inproceedings{kiaghadi2022fabtoys,
title = {FabToys: plush toys with large arrays of fabric-based pressure sensors to enable fine-grained interaction detection},
author = {Ali Kiaghadi and Jin Huang and Seyedeh Zohreh Homayounfar and Trisha Andrew and Deepak Ganesan},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services},
pages = {1--13},
abstract = {Recent advances in fabric-based sensors have made it possible to densely instrument textile surfaces on smart toys without changing their look and feel. While such surfaces can be instrumented with traditional sensors, rigid elements change the nature of interaction and diminish the appeal of plush toys.
In this work, we propose FabToy, a plush toy instrumented with a 24-sensor array of fabric-based pressure sensors located beneath the surface of the toy to have dense spatial sensing coverage while maintaining the natural feel of fabric and softness of the toy. We optimize both the hardware and software pipeline to reduce overall power consumption while achieving high accuracy in detecting a wide range of interactions at different regions of the toy. Our contributions include a) sensor array fabrication to maximize coverage and dynamic range, b) data acquisition and triggering methods to minimize the cost of sampling a large number of channels, and c) neural network models with early exit to optimize power consumed for computation when processing locally and autoencoder-based channel aggregation to optimize power consumed for communication when processing remotely. We demonstrate that we can achieve high accuracy of more than 83% for robustly detecting and localizing complex human interactions such as swiping, patting, holding, and tickling in different regions of the toy.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Recent advances in fabric-based sensors have made it possible to densely instrument textile surfaces on smart toys without changing their look and feel. While such surfaces can be instrumented with traditional sensors, rigid elements change the nature of interaction and diminish the appeal of plush toys.
In this work, we propose FabToy, a plush toy instrumented with a 24-sensor array of fabric-based pressure sensors located beneath the surface of the toy to have dense spatial sensing coverage while maintaining the natural feel of fabric and softness of the toy. We optimize both the hardware and software pipeline to reduce overall power consumption while achieving high accuracy in detecting a wide range of interactions at different regions of the toy. Our contributions include a) sensor array fabrication to maximize coverage and dynamic range, b) data acquisition and triggering methods to minimize the cost of sampling a large number of channels, and c) neural network models with early exit to optimize power consumed for computation when processing locally and autoencoder-based channel aggregation to optimize power consumed for communication when processing remotely. We demonstrate that we can achieve high accuracy of more than 83% for robustly detecting and localizing complex human interactions such as swiping, patting, holding, and tickling in different regions of the toy.
In this work, we propose FabToy, a plush toy instrumented with a 24-sensor array of fabric-based pressure sensors located beneath the surface of the toy to have dense spatial sensing coverage while maintaining the natural feel of fabric and softness of the toy. We optimize both the hardware and software pipeline to reduce overall power consumption while achieving high accuracy in detecting a wide range of interactions at different regions of the toy. Our contributions include a) sensor array fabrication to maximize coverage and dynamic range, b) data acquisition and triggering methods to minimize the cost of sampling a large number of channels, and c) neural network models with early exit to optimize power consumed for computation when processing locally and autoencoder-based channel aggregation to optimize power consumed for communication when processing remotely. We demonstrate that we can achieve high accuracy of more than 83% for robustly detecting and localizing complex human interactions such as swiping, patting, holding, and tickling in different regions of the toy.
2021
Andrew, Trisha L
Fabric Pressure Sensors for Longitudinal Monitoring of Human Motion in Natural Environments Inproceedings
In: ECS Meeting Abstracts, pp. 1387, IOP Publishing 2021.
@inproceedings{andrew2021fabric,
title = {Fabric Pressure Sensors for Longitudinal Monitoring of Human Motion in Natural Environments},
author = {Trisha L Andrew},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {ECS Meeting Abstracts},
number = {55},
pages = {1387},
organization = {IOP Publishing},
abstract = {Apparel with embedded self-powered sensors can revolutionize human behavior monitoring by leveraging everyday clothing as the sensing substrate. The key is to inconspicuously integrate sensing elements and portable power sources into garments while maintaining the weight, feel, comfort, function and ruggedness of familiar clothes and fabrics. We use reactive vapor coating to transform commonly-available, mass-produced fabrics, threads or premade garments into comfortably-wearable electronic devices by directly coating them with uniform and conformal films of electronically-active conjugated polymers. By carefully choosing the repeat unit structure of the polymer coating, we access a number of fiber- or fabric-based circuit components, including resistors, depletion-mode transistors, diodes, thermistors, and pseudocapacitors. Further, vapor-deposited electronic polymer films are notably wash- and wear-stable and withstand mechanically-demanding textile manufacturing routines, enabling us to use sewing, weaving, knitting or embroidery procedures to create self-powered garment sensors. We will describe our efforts in monitoring heartrate, breathing, joint motion/flexibility, gait and sleep posture using loose-fitting garments.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Apparel with embedded self-powered sensors can revolutionize human behavior monitoring by leveraging everyday clothing as the sensing substrate. The key is to inconspicuously integrate sensing elements and portable power sources into garments while maintaining the weight, feel, comfort, function and ruggedness of familiar clothes and fabrics. We use reactive vapor coating to transform commonly-available, mass-produced fabrics, threads or premade garments into comfortably-wearable electronic devices by directly coating them with uniform and conformal films of electronically-active conjugated polymers. By carefully choosing the repeat unit structure of the polymer coating, we access a number of fiber- or fabric-based circuit components, including resistors, depletion-mode transistors, diodes, thermistors, and pseudocapacitors. Further, vapor-deposited electronic polymer films are notably wash- and wear-stable and withstand mechanically-demanding textile manufacturing routines, enabling us to use sewing, weaving, knitting or embroidery procedures to create self-powered garment sensors. We will describe our efforts in monitoring heartrate, breathing, joint motion/flexibility, gait and sleep posture using loose-fitting garments.
Homayounfar, S Zohreh; Kiaghadi, Ali; Ganesan, Deepak; Andrew, Trisha L
All-Fabric Piezoionic Sensor for Simultaneous Sensing of Static and Dynamic Pressures Inproceedings
In: ECS Meeting Abstracts, pp. 1354, IOP Publishing 2021.
@inproceedings{homayounfar2021all,
title = {All-Fabric Piezoionic Sensor for Simultaneous Sensing of Static and Dynamic Pressures},
author = {S Zohreh Homayounfar and Ali Kiaghadi and Deepak Ganesan and Trisha L Andrew},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {ECS Meeting Abstracts},
number = {55},
pages = {1354},
organization = {IOP Publishing},
abstract = {The development of flexible and textile-based wearable pressure sensors has provided the opportunity of continuous and real time measurement of human physiological and biomechanical signals during daily activities. Pressure sensors are transducers that convert an exerted compression stress into a detectable electrical signal. Different transduction mechanisms have been introduced so far including triboelectricity, transistivity, capacitance, piezoelectricity, and piezoresistivity. Piezoresistive pressure sensors are the most widely used type due to the simplicity of their structure, and the wide range of materials that can be selected along with low-cost fabrication methods, and easy read-out system required for signal extraction.
A vast majority of piezoresistive sensors developed so far are on-skin sensors developed to detect subtle pressures (1 Pa-10 kPa) for touchpads and electronic skin applications. However, to sense physiological signals such as pulse, respiration, and phonation the sensor range of detection must fall within medium range of 10 kPa to 100 kPa. As expected, for larger-scale human motion detection such as sleep posture and footwear evaluation, the sensor must be able to sense compression stresses larger than 100 kPa. This wide range of detection required by the piezoresistive pressure sensors is one of the important challenges in designing these sensors.
Many of the piezoresistive sensors function based on employing the composite of conductive additives in an elastomer as an active layer. The functionality and sensitivity of these sensors are highly limited by the poor bulk mechanical properties of the elastomer in addition to unbreathability and the complications arising from the skin-sensor interface. Textile-based sensors overcome the issues regarding the elastomer sensors to a good extend. These sensors are mainly developed through coating fibers by conductive inks or intrinsically conductive polymers (ICPs). However, these sensors suffer from major drawbacks. First, the high conductivity of the conductive coatings leads to shortening in signals upon the application of a small amount of pressure. These sensors can respond either to static or dynamic pressures and once being pressed by a pressure, completely lose their sensitivity to further pressure exertions which resembles a connection/disconnection mode of performance. Second, the sensors need to be used in tight-fitting clothing to be able to capture signals which makes it quite uncomfortable and hinders the widespread adoption of the device in society.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The development of flexible and textile-based wearable pressure sensors has provided the opportunity of continuous and real time measurement of human physiological and biomechanical signals during daily activities. Pressure sensors are transducers that convert an exerted compression stress into a detectable electrical signal. Different transduction mechanisms have been introduced so far including triboelectricity, transistivity, capacitance, piezoelectricity, and piezoresistivity. Piezoresistive pressure sensors are the most widely used type due to the simplicity of their structure, and the wide range of materials that can be selected along with low-cost fabrication methods, and easy read-out system required for signal extraction.
A vast majority of piezoresistive sensors developed so far are on-skin sensors developed to detect subtle pressures (1 Pa-10 kPa) for touchpads and electronic skin applications. However, to sense physiological signals such as pulse, respiration, and phonation the sensor range of detection must fall within medium range of 10 kPa to 100 kPa. As expected, for larger-scale human motion detection such as sleep posture and footwear evaluation, the sensor must be able to sense compression stresses larger than 100 kPa. This wide range of detection required by the piezoresistive pressure sensors is one of the important challenges in designing these sensors.
Many of the piezoresistive sensors function based on employing the composite of conductive additives in an elastomer as an active layer. The functionality and sensitivity of these sensors are highly limited by the poor bulk mechanical properties of the elastomer in addition to unbreathability and the complications arising from the skin-sensor interface. Textile-based sensors overcome the issues regarding the elastomer sensors to a good extend. These sensors are mainly developed through coating fibers by conductive inks or intrinsically conductive polymers (ICPs). However, these sensors suffer from major drawbacks. First, the high conductivity of the conductive coatings leads to shortening in signals upon the application of a small amount of pressure. These sensors can respond either to static or dynamic pressures and once being pressed by a pressure, completely lose their sensitivity to further pressure exertions which resembles a connection/disconnection mode of performance. Second, the sensors need to be used in tight-fitting clothing to be able to capture signals which makes it quite uncomfortable and hinders the widespread adoption of the device in society.
A vast majority of piezoresistive sensors developed so far are on-skin sensors developed to detect subtle pressures (1 Pa-10 kPa) for touchpads and electronic skin applications. However, to sense physiological signals such as pulse, respiration, and phonation the sensor range of detection must fall within medium range of 10 kPa to 100 kPa. As expected, for larger-scale human motion detection such as sleep posture and footwear evaluation, the sensor must be able to sense compression stresses larger than 100 kPa. This wide range of detection required by the piezoresistive pressure sensors is one of the important challenges in designing these sensors.
Many of the piezoresistive sensors function based on employing the composite of conductive additives in an elastomer as an active layer. The functionality and sensitivity of these sensors are highly limited by the poor bulk mechanical properties of the elastomer in addition to unbreathability and the complications arising from the skin-sensor interface. Textile-based sensors overcome the issues regarding the elastomer sensors to a good extend. These sensors are mainly developed through coating fibers by conductive inks or intrinsically conductive polymers (ICPs). However, these sensors suffer from major drawbacks. First, the high conductivity of the conductive coatings leads to shortening in signals upon the application of a small amount of pressure. These sensors can respond either to static or dynamic pressures and once being pressed by a pressure, completely lose their sensitivity to further pressure exertions which resembles a connection/disconnection mode of performance. Second, the sensors need to be used in tight-fitting clothing to be able to capture signals which makes it quite uncomfortable and hinders the widespread adoption of the device in society.
Homayounfar, S Zohreh; Kiaghadi, Ali; Ganesan, Deepak; Andrew, Trisha L
Materials Selection Principles for Sensing Human Motion and Physiological Signals Via Textiles Inproceedings
In: ECS Meeting Abstracts, pp. 1585, IOP Publishing 2021.
@inproceedings{homayounfar2021materials,
title = {Materials Selection Principles for Sensing Human Motion and Physiological Signals Via Textiles},
author = {S Zohreh Homayounfar and Ali Kiaghadi and Deepak Ganesan and Trisha L Andrew},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {ECS Meeting Abstracts},
number = {55},
pages = {1585},
organization = {IOP Publishing},
abstract = {The advancement of smart apparels capable of tracking human physiological signals and body locomotion have a great potential to revolutionize human performance sensing and personalized health monitoring through transforming daily life clothing into sensors. Quantitative evaluation of kinetic parameters of individual gait along with physiological signals can be employed in games and sports, as well as in diagnosis of many diseases such as Parkinson's, Multiple Sclerosis, and sleep disorders. Among different methodologies in developing wearable sensors such as inertial measurement units, textile-based electromechanical sensors encompass the majority of widely adopted applications. Electromechanical sensors fall into three major categories based on their active mechanisms: piezoelectric sensors, triboelectric sensors, and piezoresistive sensors. Recently, different combination of materials and designs have been reported to develop wearable sensors, each of which provides a unique window into a slightly different range of motion sensitivity. For example, some human signals and motions lie in the small-scale range of pressures such as those of a subtle touch, arterial pulses, and sound vibrations, while the other body movements lie in medium to large range of pressures, such as joint movements, and locomotion during sleep and intense activities. The ability to design an unobtrusive wearable sensor being highly responsive in the required range of signals calls for getting an insight into the difference between the three mechanisms of electromechanical sensing and their corresponding responses under certain conditions.
Here, we introduced a set of materials selection principles which gives researchers an in-depth insight into how to design a wearable electromechanical sensor when it comes to acquire data from a specific source of motion. In order to achieve this goal, we performed a set of purposefully designed experiments on three types of wash-stable fabric-based electromechanical sensors that had already been introduced by our lab, i.e., triboelectric sensor, piezoelectric sensor, and piezoionic sensor as a subset of piezoresistive ones. These experiments explored the effect of impact pressure, bending angle and speed, frequency, presence of a base pressure, response time, breathability, and having a multi-layer structure on the performance and sensitivity of each type of sensors. For an instance, it turned out that the triboelectric and piezoelectric sensors are a more reliable sensing element for dynamic pressures, such as joint movements, with the former being failed in the presence of a base pressure. Piezoresistive sensors are the one with the ability to sense both static and dynamic pressures, as well as being responsive under a base pressure. However, piezoresistive one would not be a choice when it comes to bending applications. Upon this comprehensive comparison, we demonstrated a conclusive map which can provide the researchers with distinguishing features of these three types of sensors to be used in corresponding niche applications.
For example, some human signals and motions lie in the small-scale range of pressures such as those of a subtle touch, arterial pulses, and sound vibrations, while the other body movements lie in medium to large range of pressures, such as joint movements, and locomotion during sleep and intense activities. The ability to design an unobtrusive wearable sensor being highly responsive in the required range of signals calls for getting an insight into the difference between the three mechanisms of electromechanical sensing and their corresponding responses under certain conditions.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The advancement of smart apparels capable of tracking human physiological signals and body locomotion have a great potential to revolutionize human performance sensing and personalized health monitoring through transforming daily life clothing into sensors. Quantitative evaluation of kinetic parameters of individual gait along with physiological signals can be employed in games and sports, as well as in diagnosis of many diseases such as Parkinson's, Multiple Sclerosis, and sleep disorders. Among different methodologies in developing wearable sensors such as inertial measurement units, textile-based electromechanical sensors encompass the majority of widely adopted applications. Electromechanical sensors fall into three major categories based on their active mechanisms: piezoelectric sensors, triboelectric sensors, and piezoresistive sensors. Recently, different combination of materials and designs have been reported to develop wearable sensors, each of which provides a unique window into a slightly different range of motion sensitivity. For example, some human signals and motions lie in the small-scale range of pressures such as those of a subtle touch, arterial pulses, and sound vibrations, while the other body movements lie in medium to large range of pressures, such as joint movements, and locomotion during sleep and intense activities. The ability to design an unobtrusive wearable sensor being highly responsive in the required range of signals calls for getting an insight into the difference between the three mechanisms of electromechanical sensing and their corresponding responses under certain conditions.
Here, we introduced a set of materials selection principles which gives researchers an in-depth insight into how to design a wearable electromechanical sensor when it comes to acquire data from a specific source of motion. In order to achieve this goal, we performed a set of purposefully designed experiments on three types of wash-stable fabric-based electromechanical sensors that had already been introduced by our lab, i.e., triboelectric sensor, piezoelectric sensor, and piezoionic sensor as a subset of piezoresistive ones. These experiments explored the effect of impact pressure, bending angle and speed, frequency, presence of a base pressure, response time, breathability, and having a multi-layer structure on the performance and sensitivity of each type of sensors. For an instance, it turned out that the triboelectric and piezoelectric sensors are a more reliable sensing element for dynamic pressures, such as joint movements, with the former being failed in the presence of a base pressure. Piezoresistive sensors are the one with the ability to sense both static and dynamic pressures, as well as being responsive under a base pressure. However, piezoresistive one would not be a choice when it comes to bending applications. Upon this comprehensive comparison, we demonstrated a conclusive map which can provide the researchers with distinguishing features of these three types of sensors to be used in corresponding niche applications.
For example, some human signals and motions lie in the small-scale range of pressures such as those of a subtle touch, arterial pulses, and sound vibrations, while the other body movements lie in medium to large range of pressures, such as joint movements, and locomotion during sleep and intense activities. The ability to design an unobtrusive wearable sensor being highly responsive in the required range of signals calls for getting an insight into the difference between the three mechanisms of electromechanical sensing and their corresponding responses under certain conditions.
Here, we introduced a set of materials selection principles which gives researchers an in-depth insight into how to design a wearable electromechanical sensor when it comes to acquire data from a specific source of motion. In order to achieve this goal, we performed a set of purposefully designed experiments on three types of wash-stable fabric-based electromechanical sensors that had already been introduced by our lab, i.e., triboelectric sensor, piezoelectric sensor, and piezoionic sensor as a subset of piezoresistive ones. These experiments explored the effect of impact pressure, bending angle and speed, frequency, presence of a base pressure, response time, breathability, and having a multi-layer structure on the performance and sensitivity of each type of sensors. For an instance, it turned out that the triboelectric and piezoelectric sensors are a more reliable sensing element for dynamic pressures, such as joint movements, with the former being failed in the presence of a base pressure. Piezoresistive sensors are the one with the ability to sense both static and dynamic pressures, as well as being responsive under a base pressure. However, piezoresistive one would not be a choice when it comes to bending applications. Upon this comprehensive comparison, we demonstrated a conclusive map which can provide the researchers with distinguishing features of these three types of sensors to be used in corresponding niche applications.
For example, some human signals and motions lie in the small-scale range of pressures such as those of a subtle touch, arterial pulses, and sound vibrations, while the other body movements lie in medium to large range of pressures, such as joint movements, and locomotion during sleep and intense activities. The ability to design an unobtrusive wearable sensor being highly responsive in the required range of signals calls for getting an insight into the difference between the three mechanisms of electromechanical sensing and their corresponding responses under certain conditions.
