1. Download Handbook Of Environmental Acoustics Inc Campus
2. Download Handbook Of Environmental Acoustics Inc Camp Springs

Here is an unsorted list of online engineering books available for free download. There are books covering wide areas of electrical and electronic engineering, mechanical engineering, materials science, civil engineering, chemical and bioengineering, telecommunications, signal processing, etc.

What if you could adjust the volume of life itself? No more flights filled with crying babies.

No more risk of your ears falling off at that concert. No more loud neighbors Only the sounds you like to hear, when you want to hear them.

Well, hear us out. Super intended. You’ve got our attention. But no more puns, please. We are talking about Knops; the volume button for your ears. This acoustic hearing solution will give you full control over the surrounding sounds you hear.

All day every day. How do Knops work exactly? Well, it’s actually pretty darn simple. Each pair of Knops has four steps. Adjust the Knops to step one and you will hear what you would’ve heard without plugs. But the real kicker enters the stage when you switch to the other three steps.

Step 2 will reduce the volume to filter the noise of a vibrant city, step 3 will adjust the volume to a live music setting and step 4 will create a silent environment ideal for work. Four different modes for basically every audio situation. But what if I’m moving around from a busy city to a live concert and back, after which I’m in desperate need of some Zen-like silence? Aren’t you the busy bee. Just easily switch steps using the knob on the side of the Knops.

And if you like, you can instantly open up to talk to people. Say goodbye to continuous plugging and unplugging situations. Which immediately reduces the risk of losing your precious earbuds. Knops are also engineered to wear in different situations so you won’t have to worry about the buds falling out of your ears. Win win, baby. The video below shows that with a simple twist of the knob you can change the volume level of your environment. How does it work EXACTLY?

Like technically and stuff? Well, first of all Knops uses no electronics, no apps and no batteries. Instead our earbuds are acoustically engineered. The real sound is filtered using good old physics. With the help of computer simulations and real-world prototypes tested in acoustic labs, we tuned Knops.

We spend a lot of time fine-tuning the sound, so we can provide the best quality sound at every volume level. Working with the natural response of the ear canal. We even managed to create a similar reduction in dB across all the frequencies. Creating a very flat response curve.

Where did this all begin? A long time ago. In a galaxy far far away. Or, to be more exact, in 2015 in a little place we’d like to call Amsterdam. Mainly because it’s called that way.

There a group of creative friends came together to explore a solution for our hearing. We collectively decided that hearing protection devices and electronic hearables did not provide a good enough solution for our ears. And, like we mentioned earlier, they were pretty ugly. We discovered that earplugs are lowering sound all the time, most of the time with worse quality than our own natural hearing. That’s not cool.

You constantly have to unplug and replug earplugs, for a situation where sound levels are lower, or you need to communicate with your friends. Also with their design focused on hiding the plugs, they communicate that you do not want to show these products to your surrounding. Rightfully so because well, they’re ugly. Electronic hearables can provide a more better solution, however, they do not provide protection.

And that sucks. Also, because the sound goes in and out electronically, you will not hear the real sound. The sound is altered and there is a slight lag. They’re also pretty pricey because of all the electronic stuff. And although these products provide better aesthetics compared to ear plugs, we believe they still don’t look good enough to enhance the user's style.

Read: They’re ugly. After a lot of research with focus on the user experience, we created the Knops concept. A volume button, which is adaptable to every situation, protects your ears against damage, filters noise to your liking, and also looks super good.

We used a design method where we iteratively created prototypes and directly tested these with actual users in real life so we could use their feedback. This way, we involved the user from the start. We perfected the ergonomics, so you can wear Knops all day with maximum comfort. We made the turning knob work smoothly with great haptic feedback while turning. The other two founders are the brothers Arjen and Richard.

Arjen has a Ph.D. In acoustics and is a leading engineer. He has worked for clients like NASA, Porsche, and Ferrari. He’s basically a rocket scientist with an acoustic guitar.

Or something like that. The idea for Knops conceived by Arjen is also engineered by Arjen in co-operation with Richard. Richard has a master of arts and is a world class designer. He has worked with clients like IKEA and NASA. He once built a rocket named Sven. The revolutionary design for Knops is created by Richard.

Risks and challenges We have already completed most of the design and engineering for Knops and have fully working prototypes which we have tested with close partners, friends, colleagues, and a large number of independent testers. Even though we have extensively tested our prototypes, Knops is a completely new product and as with any product manufactured for the first time, there is a possibility that unforeseen bugs, challenges, and delays will occur. We will do our utmost best to deliver the perfect product. The decibel levels are indicative. We have good results with the acoustic tests of our prototypes, however the final product decibel levels may differ slightly from these indications. We will use independent test centers to qualify the official attenuation level according to norms.

We have identified our suppliers and have already started planning production timelines and processes. Moreover, through the execution success that we've had with Thunderplugs, we have proven our ability to deliver hundreds of thousands of great quality products in short timeframes. We also have our manufacturer in the Netherlands which gives us the possibility to act fast. We pride ourselves on relentless execution. Even after this Kickstarter project ends, we plan to send out continuous updates and announcements regarding Knops (and beyond!).

Physiological mechano-acoustic signals, often with frequencies and intensities that are beyond those associated with the audible range, provide information of great clinical utility. Stethoscopes and digital accelerometers in conventional packages can capture some relevant data, but neither is suitable for use in a continuous, wearable mode, and both have shortcomings associated with mechanical transduction of signals through the skin.

We report a soft, conformal class of device configured specifically for mechano-acoustic recording from the skin, capable of being used on nearly any part of the body, in forms that maximize detectable signals and allow for multimodal operation, such as electrophysiological recording. Experimental and computational studies highlight the key roles of low effective modulus and low areal mass density for effective operation in this type of measurement mode on the skin.

Demonstrations involving seismocardiography and heart murmur detection in a series of cardiac patients illustrate utility in advanced clinical diagnostics. Monitoring of pump thrombosis in ventricular assist devices provides an example in characterization of mechanical implants.

Speech recognition and human-machine interfaces represent additional demonstrated applications. These and other possibilities suggest broad-ranging uses for soft, skin-integrated digital technologies that can capture human body acoustics. INTRODUCTION Unusual classes of electronics enabled by recent advances (–) in materials science and mechanics principles can be designed with physical properties that match the soft, mechanical compliance of the skin, thereby allowing long-term (up to 2 weeks) integration with nearly any external surface of the body, with form factors that resemble those of a temporary tattoo. These systems, referred to as epidermal electronics, qualitatively expand the range of physiological measurements that are possible in wearable device platforms (–).

Many of these operational modes rely critically on an intimate, physical interface to the skin. Examples include precision measurement of temperature and thermal transport characteristics (, ), recording of electrophysiological processes and variations in electrical impedance (–), characterization of skin stiffness (, ), and monitoring of quasi-static or dynamic dimensional changes, such as those associated with swelling/deswelling or pulsatile blood flow (, ). The critical enabling properties of the devices and their interfaces with the skin include low thermal and electrical contact resistances, small thermal masses, and soft, compliant mechanics. Another (previously underused yet important) feature is that the devices can be constructed with exceptionally low mass densities, approaching those of the epidermis itself. An unexplored consequence of this characteristic is that mechano-acoustic coupling of the device to the body through the skin can be highly efficient.

The associated opportunity examined here is in precision measurements of acoustic and vibratory signatures of body processes and of mechanically active implants. Mechano-acoustic signals are known to contain essential information for clinical diagnosis and healthcare applications (, ). Specifically, mechanical waves that propagate through the tissues and fluids of the body as a result of natural physiological activity reveal characteristic signatures of individual events, such as the closure of heart valves, the contraction of skeletal muscles, the vibration of the vocal folds, and movement in the gastrointestinal tract. Frequencies of these signals could range from a fraction of 1 Hz for example, respiratory rate to 1000 Hz for example, speech (, ), often with low amplitudes beyond hearing threshold (, ). Physiological auscultation typically occurs with analog or digital stethoscopes, in individual procedures conducted during clinical examinations. An alternative approach relies on accelerometers in conventional, rigid electronic packages, typically strapped physically to the body to provide the necessary mechanical coupling.

Research demonstrations include recording of phonocardiography (PCG; sounds from the heart) , seismocardiography (SCG; vibrations of the chest induced by the beating of the heart) (–), ballistocardiography (BCG; recoil motions associated with reactions to cardiovascular pressure) (, ), and sounds associated with respiration (, ). In the context of cardiovascular health, these measurements yield important insights that complement those inferred from electrocardiography (ECG). For example, structural defects in heart valves manifest as mechano-acoustic responses and do not appear directly in ECG traces. Device design and circuit considerations The mechano-acoustic–electrophysiological sensing platform introduced here incorporates filamentary serpentine copper traces 3 μm, placed at the neutral plane between layers of polyimide (PI) encapsulation (1.2 μm) as circuit interconnects between commercial, small-scale chip components, all encapsulated above and below by an ultralow-modulus elastomeric core Silbione RT Gel 4717 A/B, Bluestar Silicone; Young’s modulus E = 5 kPa (, ). A thin layer of low-modulus silicone (Ecoflex, Smooth-On) E = 60 kPa serves as a shell ( and fig. This core/shell structure minimizes physical constrains on motions of the interconnects to improve stretchability (, –, ), and it mechanically isolates the constituent device components to reduce stresses (and associated discomfort) at the skin interface, as described previously in detail. Openings in this structure provide access to contact pads to attach a pair of electrophysiological measurement electrodes (Au, 200 nm) and a thin cable connection 100 μm; anisotropic conductive film (ACF), Elform to an external data acquisition system.

The result is a soft, skin-compatible device platform ( and fig. S2, C and D) that can accommodate significant levels of deformation without altering the operation ( and fig. S2, E and F). The direct mechanical interface to the skin, the robustness of adhesion that follows from the low-modulus construction, the low total mass, and the multifunctional operation represent key distinguishing features over previously reported wearable accelerometers. Each of these attributes is critical to the operational modes described in the following.

Schematic illustration of an epidermal mechano-acoustic–electrophysiological measurement device. The sensing circuit (fig. S1, B to D) consists of a mechano-acoustic sensor (ADXL335, Analog Devices; fig. S2, A and B), low-pass and high-pass filters, a preamplifier (TSV991A, STMicroelectronics), and removable and reusable capacitive electrodes for EP recording (fig. The sensor has a frequency bandwidth (0.5 to 550 Hz) that lies between the range of targeted cardiovascular sounds and speech. For healthy adults, the first sound (S 1) and the second sound (S 2) of the heart have acoustic frequencies of 10 to 180 Hz and 50 to 250 Hz, respectively.

Vibration frequencies of vocal folds in humans range from 90 to 2000 Hz , with an average fundamental frequency of 116 Hz (male; mean age, 19.5), 217 Hz (female; mean age, 19.5), and 226 Hz (child, ages 8 to 11) during conversation. To enable sensing of cardiac operation and speech, the cutoff frequency of the low-pass filter is 500 Hz. The high-pass filter (cutoff frequency, 15 Hz) removes motion artifacts.

Device characterization The experimental and simulation results in and figs. S4 to S11 summarize key characteristics of the materials and structures that lead to the type of soft mechanics, water-permeable, and adhesive, biocompatible surfaces needed for comfortable, robust, long-lived integration on the skin. Results in fig.

S4A show that an additional base layer of Silbione on the bottom shell surface can provide adequate adhesive force (1.16 kPa) for nondestructive and reversible attachment to skin. Measurements of the water vapor permeability (fig. S5) of Silbione, in combination with previously reported results of Ecoflex , demonstrate that the core/shell encapsulation layer has a water vapor transmission loss rate that is similar to that of widely used medical dressings (Tegaderm, 3M Medical). Cytotoxicity tests that involve culturing mouse embryonic fibroblasts (MEFs) on the surfaces of the device for 5 days demonstrate biocompatibility. Specifically, cells spread uniformly over the samples and remain attached for the duration of the assay, with no observable signs of apoptosis or necrosis. Visualizing cells at 1-, 3-, and 5-day time points by staining with calcein AM and ethidium homodimer-1 indicates 95% viability after 5 days (fig. Experimental studies and three-dimensional finite element analysis (3D-FEA) of the system under a biaxial strain of 25% allow for the examination of the mechanics at levels of deformation that exceed those likely to be encountered on the skin.

Optical images and corresponding simulation results in show good agreement. The strain contour in the upper layer of indicates that the maximum principal strains in most locations are below 1%.

Large strains (2.5%), still below the fracture threshold of the PI/Cu/PI system, occur only in certain regions of the interconnects, highlighted by the red dashed box. These strains can be reduced by increasing the interconnect lengths or the thickness of the core encapsulation material. Shows a magnified view of this region, where the influence of two adjacent components leads to a local region of strain concentration.

The calculated strains are lower than the fracture strain of copper (5%), indicating a total biaxial stretchability of the device that is larger than 25%. Consistent with previous studies, stretching is mainly absorbed by deformations of the serpentine interconnects.

Assuming a yield strain of 0.3% in the copper, the elastic stretchability in both directions is 4.6%. Results of 3D-FEA for an otherwise identical system, but without any of the device components, appear in fig. The deformation patterns also show good agreement with experiment when biaxially stretched by 25%, with a similar strain concentration effect observed in the same region. Stress-strain measurements along the device length (fig.

S8) reveal effective moduli of 32.1 kPa (with chips) and 8.68 kPa (without chips), which are much smaller than those of the epidermis (100 to 200 kPa), and confirm the stretchability of up to 25% strain. The layouts can be adjusted to meet application requirements. The mechano-acoustic response captured without analog filters using a vibration simulator (3B Scientific) shows the expected frequency bandwidth (fig. For use on the body, the depth of the source varies according to the location and the associated organ. As examples, the larynx is 5 mm below the surface of the neck, and the valves of the heart are 30 mm away from the surface of the chest. In vitro experiments use fresh pieces of chicken breast, with thicknesses between 1 and 30 mm, placed between the sensor and the vibration simulator to simulate the effects of viscoelastic losses.

Results indicate that the spectral power of the measured response exhibits a power law behavior with respect to signal frequency and an asymptotic decay with respect to tissue thickness , as expected from the acoustic attenuation (, ) by absorption and scattering in viscoelastic materials and at the materials interfaces (–). The average decrease in spectral power between frequencies in the measurement range is 51% on 1-mm-thick tissue and 83% on 30-mm-thick tissue. Partly because of this attenuation and partly because of the small amplitudes at the biological source, mechano-acoustic signals at the surface of the skin are relatively weak, and increasingly so with increasing frequency.

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Therefore, measurements must account for effects in mechanical loading and mechanical impedance matching between the devices and the skin. The mass of the sensor system is an important characteristic in this regard. Increasing the device mass increases the mechanical loading at the skin interface, thereby decreasing the mechano-acoustic motions. In vitro experiments to demonstrate these effects involve experiments such as those described above but with the sensor placed in an acrylic box (19 mm × 42.5 mm × 55 mm, 9.36 g) with different added test masses. Results in (A to C) and fig. S10 show a general trend of decreasing spectral power with tissue thickness and mass for all frequencies within the accelerometer bandwidth.

The additional mass in this case has negligible effect. A simple mechanical model consisting of a mass, a spring, and a damping source (note S1) can capture the overall behaviors.

The computed results at three different frequencies (50, 100, and 200 Hz) indicate that the response decreases with increasing mass, tissue thickness, and frequency (fig. In vivo studies of speech recognition confirm that increasing mass leads to decreasing signal. Summary of the experimental and computational studies of the effects of device mass, modulus, tissue thickness, and signal frequency on measured mechano-acoustic responses. In addition to overall device mass, the distribution of this mass and the overall mechanics of the structure are important. In particular, in a soft, low-modulus device platform, only the mass of the mechano-acoustic sensor chip is important, whereas in a rigid platform, the overall mass limits the performance.

Results in verify that in a low-modulus device platform, added mass is only significant when located at the position of the sensor, and that added mass at different locations has similar loading effects for the case of a rigid platform. FEA of a similar system (note S2) is consistent with the experimental data (fig. These findings suggest that low-mass and low-modulus characteristics are critically important. An additional implication is that, in the physical forms reported here, batteries, radios, and other components of interest for future embodiments can be included in the platform without adversely affecting the measurement sensitivity. Seismocardiography measurement Seismocardiography (SCG) captures the thoracic vibrations from atroventricular contractions and blood ejection into the vascular tree on the skin of the sternum (, ). Each beat cycle produces a characteristic SCG complex as a quasi-periodic waveform with frequency components that reflect contraction of the heart muscle and associated ejection of blood.

Shows the mechano-acoustic device and its pair of conformal capacitive electrodes laminated onto the sternum for simultaneuous measurements of SCG and ECG. Application of mechano-acoustic–electrophysiological sensing with an epidermal device in diagnosing cardiovascular health status. A single cardiac cycle includes systole (contraction of heart muscle) and diastole (relaxation of heart muscle) motions of the atria and the ventricles, as illustrated in. These motions involve electrical signals followed by mechanical coupling and a sequence of mechano-acoustic signatures as the heart chambers contract and the valves close.

These electrophysiological and mechanical data form the basis of ECGs and cardiac auscultations, respectively. Shows ECG and SCG signals measured simultaneously from a healthy male subject (age, 22). Magnified views of a single cardiac cycle highlight all the key features of these two waveforms. This information is useful in the assessment of systolic and diastolic ventricular function. For example, the electromechanical activation time (the time interval from the onset of the QRS to the point of peak intensity of S 1) corresponds to the time required for the left ventricle (LV) to achieve sufficient pressure to force the mitral valve to close.

Its prolongation indicates systolic heart failure. Reductions in the interval between S 1 and S 2 (termed left ventricular systolic time) are a sign of LV dysfunction. Overall, the data from the epidermal mechano-acoustic sensors reported here have a quality comparable to that of the data obtained using a commercial electronic stethoscope (JABES Electronic Stethoscope, GS Technology Co.), where S 1 and S 2 are delineated.

This device can also measure pressure pulse waves associated with arterial blood flow. A sensor placed on the carotid artery at the neck (fig.

S12) can capture these data, along with ECG signals. For subjects with cardiovascular pathologies, murmurs are often present in addition to signatures associated with S 1 and S 2. The holosystolic murmurs of the mitral and tricuspid valve regurgitation that occur during systole have acoustic signatures of characteristic constant intensity and high frequency. In constrast, diastolic murmurs are often detected in patients with aortic or pulmonic valve regurgitation (, ). Clinical validation of the device operation in this context involves recording cardiac mechano-acoustic responses with ECG signals from eight patient volunteers diagnosed with cardiac valvular stenosis or regurgitation.

Shows the auscultation mounting sites that yield optimal results for the aortic, pulmonary, tricuspid, and mitral heart valves. An elderly female patient (age, 78) with diagnosed mild tricuspid and pulmonary regurgitation via echocardiography (fig. S13) manifests a short, constant intensity murmur at tricuspid and pulmonary sites in systole and diastole, respectively, as indicated by the arrows in (G to J). Measurement from the aortic site shows no signs of stenosis or regurgitation. Signal from the mitral site is weak, likely because of nonoptimal sensor placement.

Figure S14 shows a female patient (age, 82) with severe regurgitation of the tricuspid and mitral valve and an irregular beat rate. Studies on other related patients yield similar data. Acoustic analysis of VAD Additional biomedical applications include monitoring of mechanical circulatory support devices, such as those that augment dysfunctional ventricular pump function and serve as important temporary or permanent alternatives to heart transplantation. The latest continuous-flow left ventricular assist devices (LVADs) offer improved durability and hemodynamic restoration, though with the limitation of adverse events, including a loss of pump function due to pump thrombosis or other mechanical failure. Previous work in the context of the first failure mode shows that the formation of blood clots on the rotor leads to changes in the sounds of the pump (–).

These changes can be difficult or impossible to discern using stethoscopes or unaided human hearing, particularly for early-stage thrombosis. The mechano-acoustic sensors reported here enable a surface-mounted mode to monitor changes in vibration signatures in the LVAD pump. Studies reported here focus on an in vitro model with a commercial LVAD (HeartMate II, Thoratec Corporation) and continuous flow to detect changes in acoustic signal correlating to variation in pump speed, circulating fluid, and thrombus embolization. Figure S15A shows a system consisting of a circulatory closed loop that involves medical grade tubing (Tygon) connected to HeartMate II, with valves to assist in the removal of air bubbles and to allow the introduction of blood clots. The device laminates conformally onto the metal housing of the pump impeller and brushless dc motor to provide direct measurements of vibration.

The spectral power of the signal collected for a short time (30 s) during operation of HeartMate II at 8400 rpm appears in. The bottom panel in shows characteristic signatures at 139.7 Hz (peak A) and 166 Hz (peak B) and its second harmonic at 332 Hz.

Increasing the pump speed from 8400 to 9400 rpm leads to decreases in the frequency of peak A from 139.7 to 156.2 Hz , whereas peak B remains unchanged. These data suggest that peak A can serve as a reliable indication of the pump speed. Replacing water with glycerol, a fluid medium with a viscosity similar to that of blood serum but higher than that of water, leads to no significant change in the acoustic signature. This result suggests that the pump rotation dominates collected acoustic signatures, and that they are insensitive to changes in circulating fluid viscosity. Application of mechano-acoustic sensing with an epidermal device in diagnosing VAD operation.

Introducing a blood clot (500 μl) (fig. S15B) prepared from bovine whole blood through the air valve at the inflow of the HeartMate II during glycerol operation at 9400 rpm serves to simulate thrombosis and embolization. Immediately after injection, the blood clot travels through the LVAD and exits the outflow tubing with minimal distortion. The associated widening of peak A suggests that clot interaction with the pump impeller produces additional frequencies (, top panel).

While the clot travels through the remainder of the circulation loop, the pump remains undisturbed, and the vibration signature returns to its initial, that is, two-peak state, but with peak A at a higher amplitude than peak B (, second panel), possibly as a result of tiny blood clots attached to the pump impeller. After several passages, the clot dissipates completely into microscopic fragments invisible to the unaided eye.

This process creates another strong group of frequencies around peak A (, third panel). Finally, the vibration signature restores to the circulation state, with peak A again at higher amplitude, confirming previous observation (, bottom panel). These results serve as a reference that validates the possible use of an accelerometer to capture acoustic signatures in the LVAD for pump thrombosis detection and monitoring. Application of mechano-acoustic sensing with an epidermal device for speech recognition. First, with appropriate placement, epidermal mechano-acoustic devices can simultaneously capture both electromyogram (EMG) signals from articulator muscle groups and acoustic vibrations from the vocal cords. Shows EMG signals (top) and mechano-acoustic vibrations (bottom) recorded while speaking “left,” “right,” “up,” and “down.” The spectrogram (, top left) highlights the unique time-frequency characteristics of each of the four words. The low-frequency components of the nasal consonant in “down” are particularly prominent.

Previous research suggests that the fusion of multiple sensors can improve speech recognition (–). A specific suggestion is that throat EMG can enhance traditional speech recognition techniques (, ), although simultaneous recording of EMG and acoustics in a single device has not been demonstrated. An earlier study showed that fusion of acoustic data with EMG signals measured using separate devices improved word recognition accuracy in a small group of patients with dysarthria. Second, the intimate contact between the sensors and the skin renders their operation almost unaffected by ambient acoustic noise. Compares spectrograms of speech (“left,” “right,” “up,” and “down”) recorded by an epidermal sensor and by a standard microphone (iPhone, Apple Inc.; see fig. S16 for time domain data), both attached to a subject’s throat.

The noise source (radio speakers) is 2.5 m away from the subject. In a quiet environment 30 dB , both the epidermal sensor and the microphone show similar responses. On the other hand, a noisy environment 60 dB significantly degrades the quality of recording from the microphone but does not affect the epidermal sensor. This feature could allow the epidermal acoustic sensor to be used for communication in loud environments by first responders , ground controllers, or security agents. A simple isolated word detection system, used in real time to play a Pac-Man game, demonstrates the potential of the epidermal acoustic sensor for human-machine interfaces. Figure S17 shows the signal flow for a control system for the isolated word detection system. Implementation begins with a training phase based on four commands: “left,” “right,” “up,” and “down,” Preprocessing involves implementation of noise reduction techniques shown in fig.

S18, which does not alter classification accuracy. Classification occurs in real time using linear discriminant analysis (LDA). A confusion matrix summarizes the accuracy of this classifier, in which the columns represent the predicted word and the rows represent the targeted word. In this example, the recognition accuracy is 90%. Further improvements are possible through additional training, different classification methods , and a wider passband on the sensor.

A video of a user playing a Pac-Man game appears in video S3; these same speech recognition strategies can be applied to almost any type of human-machine interfaces, such as drone and prosthesis control (, ). Possibilities in digital authentication appear in fig.

DISCUSSION The class of device reported here exploits a thin, lightweight, low-modulus, and skin-compatible architecture to enable mechano-acoustic sensing. These physical attributes, although important for wearability and comfort in previous types of “epidermal” technologies, represent critical enabling features for such systems because they allow high-fidelity mechanical coupling across the skin/device interface. The results create many opportunities in precision recording of sounds and vibratory signatures not only of natural body processes but also of the operation of mechanical implants, such as LVADs. Bench studies and simulation results highlight the fundamental physics associated with this type of sensing. A range of uses with human subjects—in contexts spanning the characterization of heart murmurs in patients known to have either regurgitation or stenosis at defined valvular listening areas (for example, tricuspid or aortic) to machine interfaces in real-time control of computer gaming systems—foreshadows some of the broad opportunities of these concepts. Other potential clinical applications include heart rate variability analysis, beat-to-beat assessment of the pre-ejection period, and left ventricular ejection time. Body sounds, such as snoring, respiration, and gastrointestinal tract movement, are also of some interest.

In many cases, fully wireless capabilities in data transfer, on-board data storage/processing, and integrated power supply will be necessary, particularly for applications that require continuous, untethered operation. Preliminary data (fig. S20) indicate that the most advanced commercial skin-mounted devices with these features (BioStampRC, MC10 Inc.) offer areal mass densities and low-modulus designs that are sufficient to allow similar levels of mechano-acoustic sensing, as well as multifunctional operation in EP recording. Further optimization of the mechanics and mass distributions associated with this platform, using the design rules outlined here, and further exploration of its use in clinical applications to establish a catalog of pathological functions and conditions represent promising directions for future research. Fabrication of epidermal mechano-acoustic device The fabrication process involves three parts: (i) patterning of the circuit interconnects; (ii) transfer-printing and chip-bonding onto a soft, core/shell substrate; and (iii) covering the top surface with a similar soft core/shell structure.

Fabrication of the interconnects began with a commercial laminate (MicroThin, Oak-Mitsui Inc.) that contains a copper carrier film (17.5 μm) and a thin copper foil (3 μm) separated by a release layer. Spin-coating and thermal curing formed a film of PI (1.2 μm; PI 2545, HD MicroSystems) on the side with the thin copper foil (3 μm). Peeling this PI-coated layer from the thick copper layer allowed its attachment onto a glass slide coated with poly(dimethylsiloxane) (sylgard 184, Dow Corning).

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The following describes the fabrication process in more detail: (i) Photolithography and metal etching defined a pattern of interconnects in the copper. Another spin-coating and curing process yielded a uniform layer of PI on the resulting pattern. Photolithography and reactive ion etching (RIE, Nordson MARCH) defined the top and bottom layers of PI in geometries matching those of the interconnects. (ii) A piece of water-soluble tape (Aquasol) enabled the transfer of these encapsulated interconnects onto a trilayer film supported by a silicon wafer, prepared by spin-coating (4000 rpm) and curing a thin layer of an ultrasoft silicone (Silbione, RT Gel 4717 A/B, Bluestar Silicones), followed by a layer of slightly stiffer silicone (Ecoflex, 00-30, Smooth-On) at 1000 rpm and, finally, another layer of ultrasoft silicone at 1000 rpm. This trilayer defined the skin-adhesive interface and the core/shell substrate. Removal of the tape by immersion in water exposed the interconnects to allow bonding of the device components onto designated pads using solder paste (Indalloy 290, Indium Corporation) and a heat gun at 165°C.

(iii) Encapsulation began with manual placement of cured, individual pieces of silicone onto the pads that connect to the ECG electrodes and to those that interface to the ACF cable. Spin-coating (1000 rpm) and curing a layer of Silbione followed by a layer of Ecoflex at 1000 rpm defined the core/shell superstrate. Removal of the silicone pieces completed the fabrication process.

Attachment of the ACF cable and ECG electrodes occurred just before mounting the device on the skin. Adhesion strength tests. Standard vertical peel measurements defined the adhesion strength between test samples and the skin on the flexor muscle. Each sample (2.5 cm × 2.5 cm, 1 mm thick) was prepared by mixing monomer and curing agent components for Silbione and Ecoflex and then thermally curing the materials.

The bilayer structure consisted of a 500-μm-thick layer of Ecoflex on a glass substrate, with a 500-μm-thick layer of Silbione on top. The test substrate was placed on the skin, and a corner was attached to the hook of a force gauge at 90° (Mark-10). The reported strength of adhesion corresponds to the measured force divided by the substrate area. Water vapor transmission loss test. Measurements of water vapor loss follow the standards in ASTM E96-95.

Films of Silbione were prepared by spin-coating at 250, 500, 1000, and 2000 rpm on the wafer substrate. Flasks (125 ml) were filled with dry cobalt chloride (Drierite) at equal weight and sealed with the Silbione/Ecoflex films using plastic bands (fig. Changes in weight of each flask were recorded daily for 6 days at room temperature (23°C) and 50% humidity.

The water vapor transmission rates are based on these measurements. Cell viability assay. MEFs were obtained from K.

Kilian’s laboratory. MEFs were isolated from embryos 13 days after coitus with 0.05% Trypsin (Gibco).

Cells were cultured in high-glucose Dulbecco’s Modified Eagle’s Medium (DMEM) (4.5 g/ml) supplemented with 10% fetal bovine serum (Sigma) and 1% penicillin/streptomycin. The medium was changed every 3 days and passaged at 80% confluency. Device samples were sterilized by autoclaving the samples at 121°C for 60 min, followed by exposing them to ultraviolet irradiation for 30 min, and finally by washing them in phosphate-buffered saline (PBS).

The device surface was exposed to laminin (25 μg/ml; Sigma L2020) in PBS for 30 min and then transferred to a six-well plate. MEFs were seeded on samples at an initial concentration of 20,000 cells/ml and cultured for 5 days. After 1, 3, and 5 days in culture, devices were incubated with Hoechst 33342 (1 μg/ml), calcein AM (2 μM), and ethidium homodimer-1 (4 μM) in PBS solution for 20 min. Samples were mounted onto glass slides and imaged with an IN Cell Analyzer 2000 (GE). Immunofluorescent images were analyzed using ImageJ software.

Measurements of cell viability correspond to the proportion of live cells (green) over all cells (green + red). Cells grown on tissue culture plastic in standard DMEM and in DMEM with 10% dimethyl sulfoxide served as positive and negative controls, respectively. Vibration response. Tests involved attaching the devices, without analog low- and high-pass filters, to a flat aluminum stand mounted on a vibration generator (3B Scientific). The vibration was generated by a 1-cm pole connected to the diaphragm of a loudspeaker (50 W, 100 mm, 8 ohm; SR 1010, Somogyi) fitted inside a plastic housing.

The square wave output of a function generator (FG100, 3B Scientific) provided a 3-V output to the loudspeaker at discrete frequencies of 1, 5, 10, 50, 100, 250, and 500 Hz. A commercial system (PowerLab, ADInstruments) enabled data acquisition, without filters, at a sampling rate of 1 kHz. Measurements of the influence of tissue thickness used fresh chicken breast (Miller Amish Poultry) sliced into 2 cm × 2 cm pieces at thicknesses of 1, 5, 10, and 30 mm. When inserted between the sensor and the vibration stand (4 cm × 4 cm), the moist surfaces of the tissue ensured sufficient adhesion to prevent relative movement during vibration, using square waves with an amplitude of 3.7 V and frequencies of 50, 100, 200, 300, 400, and 480 Hz. The effect of mass and tissue thickness was determined using the same experimental setups described above. The sensor was taped firmly to the bottom center of an acrylic box (19 mm × 42.5 mm × 55 mm, 9.36 g). Medical tape (silicone tape, 3M Medical) wrapped onto the vibration stand stabilized the box on the chicken tissue.

Screw nuts (3/8 inch, 1.38 g) were used as elements for added mass, fixed firmly to the top cover of the acrylic box by a double-sided adhesive. Speech sensing was evaluated using a sensor placed in the acrylic box as described above. Measurements involved acoustic vibrations associated with a subject saying “left,” with different added masses. The acrylic box was attached to the subject’s throat via a double-sided adhesive between the skin and the box interface and medical tape on top of the box.

To study the effect of mass location, a set of four mass elements was connected in a column and attached to the middle, upper right, upper left, lower right, and lower left locations of the bottom of the box. Mechanical modeling and FEA 3D-FEA simulations based on commercial software packages (Abaqus 6.14, Dassault Systemes) guided the optimization of the mechanics of the system. The elastomers were modeled by eight-node, 3D hexahedron elements (C3D8R). The electronic chips, serpentine interconnects, and PI layers were modeled by four-node shell elements (S4R). Displacement boundary conditions applied to the substrate allowed the system to be stretched. The Young’s modulus ( E) and Poisson’s ratio (ν) of the materials were as follows: for Silbione, E Silbione = 5 kPa and ν Silbione = 0.48; for Ecoflex, E Ecoflex = 60 kPa and ν Ecoflex = 0.48; for PI, E PI = 2.5 GPa and ν PI = 0.34; and for copper, E Cu = 119 GPa and ν Cu = 0.35. FEA using Abaqus also determined the effects of frequency, mass, and tissue thickness on the mechano-acoustic signal.

Here, C3D8R were used to model the tissue, the mass objects, and the accelerator, all under a sinusoidal force input. The tissue was modeled as a viscoelastic solid, with a Young’s modulus of 0.18 MPa and a Prony series function with constants g i = k i = 0.91001 s and τ i = 0.9899 s. After frequency analysis of the whole system, modal dynamic was chosen as the analysis method to simulate system vibration.

Demonstrations of seismocardiography Clinical tests at Camp Lowell Cardiology involved eight elderly patients as volunteers, all providing informed consent. Optimal sensor placement sites at traditional aortic, pulmonary, tricuspid, and mitral locations were determined by ultrasound probes, with verification of heart murmurs by echocardiogram (GE Healthcare). A three-lead setup enabled simultaneous recording of ECG using the same device platform. PowerLab system (8/35, ADInstruments) with BioAmp modules served as the hardware for data acquisition and analysis. During measurement, the subject was asked to “stop breathing” for 3 s and then to “breathe normally” after a verbal countdown to eliminate the respiratory effect on the baseline and amplitude of the SCG data. Passing the output of the accelerometer through a 20-Hz low-pass digital filter followed by an analog-to-digital converter in the PowerLab system yielded processed data at a sampling rate of 1 kHz.

A band-pass digital filter with a low cutoff and a high cutoff frequency of 1 and 30 Hz, respectively, was used with the ECG signal. All vibration signals were converted from output voltage to “mechano-acoustic response (arbitrary units).”. Measurements from LVADs The test platform consisted of a closed loop created by connecting a commercial LVAD (HeartMate II, Thoratec Inc.) and its respective driver by 1 m of medical grade tubing (Tygon) at the inlet and outlet, with syringe ports at each location for the introduction of water, without air bubbles. Tape secured the device to the housing of the LVAD. Baseline studies involved measurements of vibration during the operation of the LVAD at various speeds between 8400 and 9400 rpm, with 200-rpm increments.

Additional similar experiments used 30% (v/v) glycerol in water. Studies on the effects of VAD thrombosis used fresh blood clots formed via addition of calcium chloride added to 10% (v/v) acid citrate dextrose in fresh bovine whole blood, with the aim of reaching a concentration of 25 mM. Blood clots formed spontaneously during storage overnight at room temperature.

Clots with weights of 250 mg were introduced into the closed loop before activating the LVAD. The sensor response was recorded during circulation of a single clot while operating the LVAD at 9400 rpm. Additional similar experiments used 30% (v/v) glycerol in water. Algorithms for the classification of data related to speech Real-time classification of speech signals relied on a simple four-class (left, right, up, and down) isolated word recognition system with a “null” state. Before classification, the data were preprocessed to reduce ambient noise using spectral subtraction and then digitally filtered, using an eighth-order Butterworth filter, from 30 to 1000 Hz.

The resulting data were defined as null unless the root mean square value surpassed a threshold. Analyzing the energy of the signal in a sliding 50-ms window enabled determination of the exact onset and offset of the word.

Fourier transformation with a 100-ms time window and a 70-ms overlap defined the time-frequency estimate of the data during the duration of the word. The results were averaged and reduced in dimensionality using principal components analysis to form a feature vector. This feature vector was finally classified using LDA.

Training involved 20 trials from each class, with 90% accuracy. The resulting classifier enabled real-time operation in a simple video game.

We thank Camp Lowell Cardiology (M. Goldberg and K. Aiken) for affording clinical patient access and echocardiography support for this study.

Thanks J.A.R. For their continuous mentoring and support.

Device fabrication and development were carried out in part at the Frederick Seitz Materials Research Laboratory Central Research Facilities, University of Illinois. Funding: Y.L. Acknowledges support from Systems on Nanoscale Information Fabrics (SONIC), one of the six Semiconductor Research Corporation STARnet Centers, sponsored by MARCO and DARPA. Acknowledges start-up funding from the University of Colorado Boulder. Author contributions: Conception, design, and study direction: Y.L., Y.H., J.-W.J., and J.A.R.

Device fabrication: Y.L., R.Q., H.L., L.Y., J.W.L., and J.-W.J. Experimental validation: Y.L., J.J.S.N., R.Q., K.R.A., K.-I.J., D.Z., K.A.K., P.L.T., S.H.J., T.B., M.J.S., J.-W.J., and J.A.R. Data analysis: Y.L., J.J.S.N., J.-W.J., and J.A.R. Theoretical modeling: Y.L., Z.Z., J.X., and Y.H. Manuscript writing: Y.L., J.J.S.N., K.R.A., D.Z., J.X., Y.H., J.-W.J., and J.A.R.

Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.

Any additional data sets, analysis details, and material recipes are available upon request. Supplementary material for this article is available at note S1. Analytical model for mass effect on acceleration. Effect of low-modulus device substrate.

Device design and circuit layouts. Computed x-ray tomography images of the internal structures of the accelerometer chip. Schematic illustration of capacitive ECG electrodes and demonstrations of their reusability. Adhesion strength of Silbione to the skin and dependence of its thickness on spin speed.

Measurements of water vapor transmission loss. Cell viability assay and cytotoxicity test. Mechanical simulation of the circuit interconnects during biaxial stretching. Stress-strain response of the device.

Vibration response of the accelerometer chip without analog filters. Comparison of experimental and simulation results on the effect of mass, tissue thickness, and signal frequency on measurement response.

Schematic illustration and measurement results of the vibration model to capture the effects of device modulus. Application of an epidermal mechano-acoustic–electrophysiological device on the neck.

Echocardiogram characterization results on a patient with tricuspid and pulmonary regurgitation. Acoustic signals from aortic, pulmonary, tricuspid, and mitral sites of a patient with irregular heartbeat. Experiment on LVAD pump thrombosis. Data captured using a reported device and a commercial microphone in quiet and noisy environments. Data captured using a reported device and a commercial microphone in quiet and noisy environments. Process loop for a speech-based human-machine interface. Demonstration of noise reduction in time domain speech data.

Authentication application. Wireless sensing of BioStamp. Movie of speech recording in a quiet environment. Movie of speech recording in a noisy environment.

Movie of speech recognition and voice control of a Pac-Man game with real-time machine learning and signal classification.