51 research outputs found
Novel Muscle Monitoring by Radiomyography(RMG) and Application to Hand Gesture Recognition
Conventional electromyography (EMG) measures the continuous neural activity
during muscle contraction, but lacks explicit quantification of the actual
contraction. Mechanomyography (MMG) and accelerometers only measure body
surface motion, while ultrasound, CT-scan and MRI are restricted to in-clinic
snapshots. Here we propose a novel radiomyography (RMG) for continuous muscle
actuation sensing that can be wearable and touchless, capturing both
superficial and deep muscle groups. We verified RMG experimentally by a forearm
wearable sensor for detailed hand gesture recognition. We first converted the
radio sensing outputs to the time-frequency spectrogram, and then employed the
vision transformer (ViT) deep learning network as the classification model,
which can recognize 23 gestures with an average accuracy up to 99% on 8
subjects. By transfer learning, high adaptivity to user difference and sensor
variation were achieved at an average accuracy up to 97%. We further
demonstrated RMG to monitor eye and leg muscles and achieved high accuracy for
eye movement and body postures tracking. RMG can be used with synchronous EMG
to derive stimulation-actuation waveforms for many future applications in
kinesiology, physiotherapy, rehabilitation, and human-machine interface
Nanoscale Repulsive and Attractive Forces on Transistors - a Study of DNA Interaction with Non Volatile Charge
Strain and field modulation in bilayer graphene band structure
Using an external electric field, one can modulate the bandgap of Bernal
stacked bilayer graphene by breaking A-~B symmetry. We analyze strain effects
on the bilayer graphene using the extended Huckel theory and find that reduced
interlayer distance results in higher bandgap modulation, as expected.
Furthermore, above about 2.5 angstrom interlayer distance, the bandgap is
direct, follows a convex relation to electric field and saturates to a value
determined by the interlayer distance. However, below about 2.5 angstrom, the
bandgap is indirect, the trend becomes concave and a threshold electric field
is observed, which also depends on the stacking distance.Comment: 3 pages, 5 figures - v1 and v2 are the same, uploaded twice - v3,
some typos fixed and a reference adde
Armchair graphene nanoribbons: Electronic structure and electric field modulation
We report electronic structure and electric field modulation calculations in
the width direction for armchair graphene nanoribbons (acGNRs) using a
semi-empirical extended Huckel theory. Important band structure parameters are
computed, e.g. effectives masses, velocities and bandgaps. For the three types
of acGNRs, the pz orbital tight-binding parameters are extracted if feasible.
Furthermore, the effect of electric field in the width direction on acGNRs
dispersion is explored. It is shown that for the two types of semiconducting
acGNRs, an external electric field can reduce the bandgap to a few meV with
different quantitative behavior.Comment: 5 pages, 5 figure
Nonvolatile memory with molecule-engineered tunneling barriers
We report a novel field-sensitive tunneling barrier by embedding C60 in SiO2
for nonvolatile memory applications. C60 is a better choice than ultra-small
nanocrystals due to its monodispersion. Moreover, C60 provides accessible
energy levels to prompt resonant tunneling through SiO2 at high fields.
However, this process is quenched at low fields due to HOMO-LUMO gap and large
charging energy of C60. Furthermore, we demonstrate an improvement of more than
an order of magnitude in retention to program/erase time ratio for a metal
nanocrystal memory. This shows promise of engineering tunnel dielectrics by
integrating molecules in the future hybrid molecular-silicon electronics.Comment: to appear in Applied Physics Letter
An Extended Huckel Theory based Atomistic Model for Graphene Nanoelectronics
An atomistic model based on the spin-restricted extended Huckel theory (EHT)
is presented for simulating electronic structure and I-V characteristics of
graphene devices. The model is applied to zigzag and armchair graphene
nano-ribbons (GNR) with and without hydrogen passivation, as well as for
bilayer graphene. Further calculations are presented for electric fields in the
nano-ribbon width direction and in the bilayer direction to show electronic
structure modification. Finally, the EHT Hamiltonian and NEGF (Nonequilibrium
Green's function) formalism are used for a paramagnetic zigzag GNR to show
2e2/h quantum conductance.Comment: 5 pages, 8 figure
Objective dyspnea evaluation on COVID-19 patients learning from exertion-induced dyspnea scores
Objective: Dyspnea is one of the most common symptoms for many pulmonary
diseases including COVID-19. Clinical assessment of dyspnea is mainly performed
by subjective self-report, which has limited accuracy and is challenging for
continuous monitoring. The objective of this research study is to determine if
dyspnea progression in COVID patients can be assessed using a non-invasive
wearable sensor and if the findings are comparable to a learning model of
physiologically induced dyspnea on healthy subjects. Methods: Non-invasive
wearable respiratory sensors were employed to retrieve continuous respiratory
characteristics with user comfort and convenience. Overnight (~16h) respiratory
waveforms were collected on 12 COVID-19 patients, and a benchmark on 13 healthy
subjects with exertion-induced dyspnea were also performed for blind
comparison. The learning model was built from the respiratory features with
self report on 32 healthy subjects under exertion and airway blockage. Results:
High similarity between dyspnea on COVID patients and physiologically induced
dyspnea on healthy subjects was established. COVID patients have consistently
high objective dyspnea scores in comparison with normal breathing of healthy
subjects. We also exhibited continuous dyspnea scoring capability for 12-16
hours on patients. Conclusion: This paper validates the viability to use our
objective dyspnea scoring for clinical dyspnea assessment on COVID patients.
Significance: The proposed system can help the identification of dyspneic
exacerbation in conditions such as COVID, leading to early intervention and
possibly improving their outcome. This approach can be potentially applied to
other pulmonary disorders such as asthma, emphysema, and pneumonia
- …