http://www.gyenno.com/spoon-en.html
Anyone know what algorithms and components these use - to cancel out disturbances and 'distinguish intentional movement'. Could PCT do any better?
Warren
[From Bruce Abbott (2016.11.25.1020 EST)]
To distinguish "intentional" from "unintentional" movements, I imagine that
the system simply to applies a low-pass filter to the movement signals
being generated by the spoon's accelerometers to remove relatively slow
("intentional") movements from the faster ("unintentional") tremors. The
control algorithm would then move the spoon to oppose the tremors.
However, there does seem to be more to it: The system is said to be capable
of being adjusted remotely to improve its performance. I imagine that this
would involve retuning the filter to the specific tremor frequency of the
individual using the spoon (in Parkinson's, typically around 4 Hz). The
filter might even be a narrow-band pass filter that removes higher as well
as lower frequencies, thus allowing the spoon to "see" only the tremor
frequencies to which it is tuned and treat them as disturbances.
I don't see PCT as contributing anything to the spoon's design, as the spoon
already functions as a two-axis control system like those we use as models
in PCT. It's a nice control-system application.
Bruce
···
-----Original Message-----
From: Warren Mansell [mailto:wmansell@gmail.com]
Sent: Friday, November 25, 2016 4:16 AM
To: <csgnet@lists.illinois.edu> <csgnet@lists.illinois.edu>; Control Systems
Group Network <CSGNET@LISTSERV.ILLINOIS.EDU>
Cc: Henry Yin <hy43@duke.edu>
Subject: Tremor spoon
http://www.gyenno.com/spoon-en.html
Anyone know what algorithms and components these use - to cancel out
disturbances and 'distinguish intentional movement'. Could PCT do any
better?
Warren
[Martin Taylor 2016.11.25.11.07]
Given that it's an advertising web page, we have to make some
assumptions. They say it is adaptive, so my assumption is that it
does essentially what the Power Artificial Cerebellum does, i.e. to
tune the feedback against loop resonances, which is what these
tremors are. If the tremors are caused by damage to the real
cerebellum and the real cerebellum does what Powers imagined, the
spoon is reinserting in the loop what has been lost.
Martin
···
On 2016/11/25 4:15 AM, Warren Mansell
wrote:
Anyone know what algorithms and components these use - to cancel out disturbances and 'distinguish intentional movement'. Could PCT do any better? Warren
[From Rick Marken (2016.11.25.1215)]
···
Bruce Abbott (2016.11.25.1020 EST)–
BA: To distinguish “intentional” from “unintentional” movements, I imagine that the system simply to applies a low-pass filter to the movement signals being generated by the spoon’s accelerometers to remove relatively slow
(“intentional”) movements from the faster (“unintentional”) tremors. The
control algorithm would then move the spoon to oppose the tremors.
RM: I agree with this; it’s a nice proposal.
BA: However, there does seem to be more to it: The system is said to be capable of being adjusted remotely to improve its performance. I imagine that this would involve retuning the filter to the specific tremor frequency of the individual using the spoon (in Parkinson’s, typically around 4 Hz). The
filter might even be a narrow-band pass filter that removes higher as well
as lower frequencies, thus allowing the spoon to “see” only the tremor
frequencies to which it is tuned and treat them as disturbances.
RM: Yes, a band pass filter would seem best ; the system wouldn’t waste energy opposing those very high (and low) frequency components of the tremor which are probably low amplitude anyway and don’t interfere that much with the accuracy with which the spoon gets to the mouth.
BA: I don’t see PCT as contributing anything to the spoon’s design, as the spoon already functions as a two-axis control system like those we use as models in PCT. It’s a nice control-system application.
RM: I agree that PCT can’t contribute to the spoon’s design, but for different reasons. I think the main contribution PCT could make is in providing an algorithm for distinguishing the intentional from the unintentional components of the movement of spoon to mouth. This would, of course, be the algorithm of the Test for the Controlled Variable, which is used to distinguish intentional from unintentional movements in my signature (and, apparently completely underwhelming) “Mind Reading” demo (http://www.mindreadings.com/ControlDemo/Mindread.html).
RM: But there are a couple of reasons why I think this method of distinguishing intentional from unintentional behavior would not work in this situation. First, the TCV algorithm takes a while to work (as you will see if you do the demo) and you need nearly instantaneous determination of the intended movement trajectory when lifting a spoon to your mouth to correct for disturbances to that trajectory; and second, the algorithm works best when control is good (which you can also see if you do the demo; the TCV not good at detecting the intentionally moved avatar – the controlled variable – until you get pretty good at moving the avatar against the prevailing disturbances) and the problem with hand tremor is that control of the movement trajectory is poor due to the instability of the control loop. So unless the Gyenno engineers have found a way to overcome these limitations I’m pretty sure that they distinguish intentional from unintentional components of movement using the simple filtering process Bruce described.
Best
Rick
Bruce
-----Original Message-----
From: Warren Mansell [mailto:wmansell@gmail.com]
Sent: Friday, November 25, 2016 4:16 AM
To: csgnet@lists.illinois.edu csgnet@lists.illinois.edu; Control Systems
Group Network CSGNET@LISTSERV.ILLINOIS.EDU
Cc: Henry Yin hy43@duke.edu
Subject: Tremor spoon
http://www.gyenno.com/spoon-en.html
Anyone know what algorithms and components these use - to cancel out
disturbances and ‘distinguish intentional movement’. Could PCT do any
better?
Warren
–
Richard S. Marken
“The childhood of the human race is far from over. We
have a long way to go before most people will understand that what they do for
others is just as important to their well-being as what they do for
themselves.” – William T. Powers
Thanks Rick, Bruce, Andy and Martin. I had assumed that the spoon would be using negative feedback to counteract the disturbances caused by the tremor rather than any kind of filter. But are you saying that because the oscillation of the tremor is so predictable, this is not necessary? If so, what does this tell us about other disturbances in the real world?
Warren
···
Bruce Abbott (2016.11.25.1020 EST)–
BA: To distinguish “intentional” from “unintentional” movements, I imagine that the system simply to applies a low-pass filter to the movement signals being generated by the spoon’s accelerometers to remove relatively slow
(“intentional”) movements from the faster (“unintentional”) tremors. The
control algorithm would then move the spoon to oppose the tremors.
RM: I agree with this; it’s a nice proposal.
BA: However, there does seem to be more to it: The system is said to be capable of being adjusted remotely to improve its performance. I imagine that this would involve retuning the filter to the specific tremor frequency of the individual using the spoon (in Parkinson’s, typically around 4 Hz). The
filter might even be a narrow-band pass filter that removes higher as well
as lower frequencies, thus allowing the spoon to “see” only the tremor
frequencies to which it is tuned and treat them as disturbances.
RM: Yes, a band pass filter would seem best ; the system wouldn’t waste energy opposing those very high (and low) frequency components of the tremor which are probably low amplitude anyway and don’t interfere that much with the accuracy with which the spoon gets to the mouth.
BA: I don’t see PCT as contributing anything to the spoon’s design, as the spoon already functions as a two-axis control system like those we use as models in PCT. It’s a nice control-system application.
RM: I agree that PCT can’t contribute to the spoon’s design, but for different reasons. I think the main contribution PCT could make is in providing an algorithm for distinguishing the intentional from the unintentional components of the movement of spoon to mouth. This would, of course, be the algorithm of the Test for the Controlled Variable, which is used to distinguish intentional from unintentional movements in my signature (and, apparently completely underwhelming) “Mind Reading” demo (http://www.mindreadings.com/ControlDemo/Mindread.html).
RM: But there are a couple of reasons why I think this method of distinguishing intentional from unintentional behavior would not work in this situation. First, the TCV algorithm takes a while to work (as you will see if you do the demo) and you need nearly instantaneous determination of the intended movement trajectory when lifting a spoon to your mouth to correct for disturbances to that trajectory; and second, the algorithm works best when control is good (which you can also see if you do the demo; the TCV not good at detecting the intentionally moved avatar – the controlled variable – until you get pretty good at moving the avatar against the prevailing disturbances) and the problem with hand tremor is that control of the movement trajectory is poor due to the instability of the control loop. So unless the Gyenno engine
ers have found a way to overcome these limitations I’m pretty sure that they distinguish intentional from unintentional components of movement using the simple filtering process Bruce described.
Best
Rick
Bruce
-----Original Message-----
From: Warren Mansell [mailto:wmansell@gmail.com]
Sent: Friday, November 25, 2016 4:16 AM
To: csgnet@lists.illinois.edu csgnet@lists.illinois.edu; Control Systems
Group Network CSGNET@LISTSERV.ILLINOIS.EDU
Cc: Henry Yin hy43@duke.edu
Subject: Tremor spoon
http://www.gyenno.com/spoon-en.html
Anyone know what algorithms and components these use - to cancel out
disturbances and ‘distinguish intentional movement’. Could PCT do any
better?
Warren
–
Richard S. Marken
“The childhood of the human race is far from over. We
have a long way to go before most people will understand that what they do for
others is just as important to their well-being as what they do for
themselves.” – William T. Powers
[Martin Taylor 2016.11.26.00.03]
Nothing. Such tremors are usually properties of the loop. The spoon
would be changing the structure of the loop, not countering any
disturbances. It does have to do with predictability, though.
Oscillation is a sign of a feedback loop that has positive feedback
at the oscillation frequency. The properties of a loop are usually
quite stable, and thus predictable.
The Powers Artificial Cerebellum was designed to adapt to the
feedback properties of its loop, avoiding such positive feedback
conditions. Maybe the biological cerebellum does, too. I suppose
Bill thought so, since he gave the name to his adaptive device. I
wouldn’t be at all surprised if the designers of the spoon had read
Powers’s paper and implemented the AC in hardware, or improved upon
that basic design.
Martin
···
On 2016/11/25 11:18 PM, Warren Mansell
wrote:
Thanks Rick, Bruce, Andy and Martin. I had assumed that thespoon would be using negative feedback to counteract the
disturbances caused by the tremor rather than any kind of
filter. But are you saying that because the oscillation of the
tremor is so predictable, this is not necessary? If so, what
does this tell us about other disturbances in the real world?
Warren
On 25 Nov 2016, at 20:17, Richard Marken <rsmarken@gmail.com >wrote:
[From Rick Marken (2016.11.25.1215)]
Bruce Abbott(2016.11.25.1020 EST)–
BA: To distinguish "intentional" from "unintentional"movements, I imagine that the system simply to applies
a low-pass filter to the movement signals being
generated by the spoon’s accelerometers to remove
relatively slow("intentional") movements from the faster(“unintentional”) tremors. The
control algorithm would then move the spoon to opposethe tremors.
RM: I agree with this; it’s a nice proposal.
BA: However, there does seem to be more to it: Thesystem is said to be capable of being adjusted
remotely to improve its performance. I imagine that
this would involve retuning the filter to the specific
tremor frequency of the individual using the spoon (in
Parkinson’s, typically around 4 Hz). Thefilter might even be a narrow-band pass filter thatremoves higher as well
as lower frequencies, thus allowing the spoon to "see"only the tremor
frequencies to which it is tuned and treat them asdisturbances.
RM: Yes, a band pass filter would seem best ; thesystem wouldn’t waste energy opposing those very high
(and low) frequency components of the tremor which are
probably low amplitude anyway and don’t interfere that
much with the accuracy with which the spoon gets to
the mouth.
BA: I don't see PCT as contributing anything to thespoon’s design, as the spoon already functions as a
two-axis control system like those we use as models in
PCT. It’s a nice control-system application.
RM: I agree that PCT can't contribute to thespoon’s design, but for different reasons. I think the
main contribution PCT could make is in providing an
algorithm for distinguishing the intentional from the
unintentional components of the movement of spoon to
mouth. This would, of course, be the algorithm of the
Test for the Controlled Variable, which is used to
distinguish intentional from unintentional movements
in my signature (and, apparently completely
underwhelming) “Mind Reading” demo (http://www.mindreadings.com/ControlDemo/Mindread.html).
RM: But there are a couple of reasons why I thinkthis method of distinguishing intentional from
unintentional behavior would not work in this
situation. First, the TCV algorithm takes a while to
work (as you will see if you do the demo) and you need
nearly instantaneous determination of the intended
movement trajectory when lifting a spoon to your mouth
to correct for disturbances to that trajectory; and
second, the algorithm works best when control is good
(which you can also see if you do the demo; the TCV
not good at detecting the intentionally moved avatar
– the controlled variable – until you get pretty
good at moving the avatar against the prevailing
disturbances) and the problem with hand tremor is that
control of the movement trajectory is poor due to the
instability of the control loop. So unless the Gyenno
engine ers have found a way to overcome these
limitations I’m pretty sure that they distinguish
intentional from unintentional components of movement
using the simple filtering process Bruce described.
Best
Rick
Bruce -----Original Message----- From: Warren Mansell [mailto:wmansell@gmail.com] Sent: Friday, November 25, 2016 4:16 AM To: <csgnet@lists.illinois.edu ><csgnet@lists.illinois.edu >;
Control SystemsGroup Network <CSGNET@LISTSERV.ILLINOIS.EDU> Cc: Henry Yin <hy43@duke.edu> Subject: Tremor spoon [http://www.gyenno.com/spoon-en.html](https://urldefense.proofpoint.com/v2/url?u=http-3A__www.gyenno.com_spoon-2Den.html&d=DQMFaQ&c=8hUWFZcy2Z-Za5rBPlktOQ&r=-dJBNItYEMOLt6aj_KjGi2LMO_Q8QB-ZzxIZIF8DGyQ&m=2jMFz0AYe09IvqEG5h2Azu5_xc7vMDiXUCefZEsWRTI&s=eXFaVfj7GGXJfzxinbAWO5W4ZzZjADOVq3S1c44-Ljc&e=) Anyone know what algorithms and components theseuse - to cancel out
disturbances and 'distinguish intentionalmovement’. Could PCT do any
better? Warren
–
Richard S. Marken
"The childhood of the humanrace is far from over. We
have a long way to go before
most people will understand
that what they do for
others is just as important
to their well-being as what
they do for
themselves." – William T.
Powers
[From Bruce Abbott (2016.11.26.0830 EST)]
Actually, Warren, I did say that the spoon uses negative feedback to counteract disturbances caused by the tremor. (It actually does this for accelerations in both the horizontal and vertical dimensions.) The purpose of the filter is to separate the tremor-movements from those likely to be intentional movements. Because of the filter, the spoon only perceives oscillations at/near the tremor frequency and acts to oppose those by changing the angle of the spoon relative to its handle. (For example, if the tremor moves the handle vertically, the spoon bends downward to compensate; if the tremor moves the handle to the left, the spoon bends rightward to compensate.) Other movements of the spoon not at the tremor frequency would be ignored by the spoon’s control system as these would be filtered out.
Another possibility is that the spoon’s system might sense the tremor frequency based on input from its accelerometers and then generate an output of the same frequency but 180 degrees out of phase with it. The spoon’s control systems would vary the output frequency as needed to keep the phase angle of spoon movement at 180 degrees relative to handle movement and also adjust the magnitude of these oscillations to approximately equal those of the handle. Such a system would act to compensate for regular oscillations but essentially ignore non-oscillatory movements produced by the person’s “voluntary” spoon-positioning control systems.
I’m speculating, of course. The company says they borrowed the technology from the image stabilization systems of cameras. This Wikipedia page describes several of these techniques: https://en.wikipedia.org/wiki/Image_stabilization . The one that induces yaw and pitch of the lens to compensate for the camera body’s accelerations seems to be the one that matches the way the spoon operates, with its changes in angle relative to its handle. But there must be something additional so that the spoon does not try to compensate for “intentional” movements – cameras with image stabilization try to compensate for the motion induced when the photographer intentionally “pans” the camera. (The Wikipedia article describes recent versions that detect panning and temporarily disable horizontal shake-compensation.)
Bruce
···
From: Warren Mansell [mailto:wmansell@gmail.com]
Sent: Friday, November 25, 2016 11:19 PM
To: csgnet@lists.illinois.edu
Cc: Maximilian Parker maximilian.parker@postgrad.manchester.ac.uk; Andrew Weightman andrew.weightman@manchester.ac.uk
Subject: Re: Tremor spoon
Thanks Rick, Bruce, Andy and Martin. I had assumed that the spoon would be using negative feedback to counteract the disturbances caused by the tremor rather than any kind of filter. But are you saying that because the oscillation of the tremor is so predictable, this is not necessary? If so, what does this tell us about other disturbances in the real world?
Warren
On 25 Nov 2016, at 20:17, Richard Marken rsmarken@gmail.com wrote:
[From Rick Marken (2016.11.25.1215)]
Bruce Abbott (2016.11.25.1020 EST)–
BA: To distinguish “intentional” from “unintentional” movements, I imagine that the system simply to applies a low-pass filter to the movement signals being generated by the spoon’s accelerometers to remove relatively slow
(“intentional”) movements from the faster (“unintentional”) tremors. The
control algorithm would then move the spoon to oppose the tremors.
RM: I agree with this; it’s a nice proposal.
BA: However, there does seem to be more to it: The system is said to be capable of being adjusted remotely to improve its performance. I imagine that this would involve retuning the filter to the specific tremor frequency of the individual using the spoon (in Parkinson’s, typically around 4 Hz). The
filter might even be a narrow-band pass filter that removes higher as well
as lower frequencies, thus allowing the spoon to “see” only the tremor
frequencies to which it is tuned and treat them as disturbances.
RM: Yes, a band pass filter would seem best ; the system wouldn’t waste energy opposing those very high (and low) frequency components of the tremor which are probably low amplitude anyway and don’t interfere that much with the accuracy with which the spoon gets to the mouth.
BA: I don’t see PCT as contributing anything to the spoon’s design, as the spoon already functions as a two-axis control system like those we use as models in PCT. It’s a nice control-system application.
RM: I agree that PCT can’t contribute to the spoon’s design, but for different reasons. I think the main contribution PCT could make is in providing an algorithm for distinguishing the intentional from the unintentional components of the movement of spoon to mouth. This would, of course, be the algorithm of the Test for the Controlled Variable, which is used to distinguish intentional from unintentional movements in my signature (and, apparently completely underwhelming) “Mind Reading” demo (http://www.mindreadings.com/ControlDemo/Mindread.html).
RM: But there are a couple of reasons why I think this method of distinguishing intentional from unintentional behavior would not work in this situation. First, the TCV algorithm takes a while to work (as you will see if you do the demo) and you need nearly instantaneous determination of the intended movement trajectory when lifting a spoon to your mouth to correct for disturbances to that trajectory; and second, the algorithm works best when control is good (which you can also see if you do the demo; the TCV not good at detecting the intentionally moved avatar – the controlled variable – until you get pretty good at moving the avatar against the prevailing disturbances) and the problem with hand tremor is that control of the movement trajectory is poor due to the instability of the control loop. So unless the Gyenno engine ers have found a way to overcome these limitations I’m pretty sure that they distinguish intentional from unintentional components of movement using the simple filtering process Bruce described.
Best
Rick
Bruce
-----Original Message-----
From: Warren Mansell [mailto:wmansell@gmail.com]
Sent: Friday, November 25, 2016 4:16 AM
To: csgnet@lists.illinois.edu csgnet@lists.illinois.edu; Control Systems
Group Network CSGNET@LISTSERV.ILLINOIS.EDU
Cc: Henry Yin hy43@duke.edu
Subject: Tremor spoonhttp://www.gyenno.com/spoon-en.html
Anyone know what algorithms and components these use - to cancel out
disturbances and ‘distinguish intentional movement’. Could PCT do any
better?
Warren
–
Richard S. Marken
“The childhood of the human race is far from over. We have a long way to go before most people will understand that what they do for others is just as important to their well-being as what they do for themselves.” – William T. Powers
[From Bruce Abbott (2016.11.26.0830 EST)]
Actually, Warren, I did say that the spoon uses negative feedback to counteract disturbances caused by the tremor. (It actually does this for accelerations in both the horizontal and vertical dimensions.) The purpose of the filter is to separate the tremor-movements from those likely to be intentional movements. Because of the filter, the spoon only perceives oscillations at/near the tremor frequency and acts to oppose those by changing the angle of the spoon relative to its handle. (For example, if the tremor moves the handle vertically, the spoon bends downward to compensate; if the tremor moves the handle to the left, the spoon bends rightward to compensate.) Other movements of the spoon not at the tremor frequency would be ignored by the spoon’s control system as these would be filtered out.
Another possibility is that the spoon’s system might sense the tremor frequency based on input from its accelerometers and then generate an output of the same frequency but 180 degrees out of phase with it. The spoon’s control systems would vary the output frequency as needed to keep the phase angle of spoon movement at 180 degrees relative to handle movement and also adjust the magnitude of these oscillations to approximately equal those of the handle. Such a system would act to compensate for regular oscillations but essentially ignore non-oscillatory movements produced by the person’s “voluntary� spoon-positioning control systems.
I’m speculating, of course. The company says they borrowed the technology from the image stabilization systems of cameras. This Wikipedia page describes several of these techniques: https://en.wikipedia.org/wiki/Image_stabilization . The one that induces yaw and pitch of the lens to compensate for the camera body’s accelerations seems to be the one that matches the way the spoon operates, with its changes in angle relative to its handle. But there must be something additional so that the spoon does not try to compensate for “intentionalâ€? movements – cameras with imagge stabilization try to compensate for the motion induced when the photographer intentionally “pansâ€? the camera. (The Wikipedia article describes recent versions that detect panning and temporarily disable horizontal shake-compensation.)
Bruce
···
From: Warren Mansell [mailto:wmansell@gmail.com]
Sent: Friday, November 25, 2016 11:19 PM
To: csgnet@lists.illinois.edu
Cc: Maximilian Parker maximilian.parker@postgrad.manchester.ac.uk; Andrew Weightman andrew.weightman@manchester.ac.uk
Subject: Re: Tremor spoon
Thanks Rick, Bruce, Andy and Martin. I had assumed that the spoon would be using negative feedback to counteract the disturbances caused by the tremor rather than any kind of filter. But are you saying that because the oscillation of the tremor is so predictable, this is not necessary? If so, what does this tell us about other disturbances in the real world?
Warren
On 25 Nov 2016, at 20:17, Richard Marken rsmarken@gmail.com wrote:
[From Rick Marken (2016.11.25.1215)]
Bruce Abbott (2016.11.25.1020 EST)–
BA: To distinguish “intentional” from “unintentional” movements, I imagine that the system simply to applies a low-pass filter to the movement signals being generated by the spoon’s accelerometers to remove relatively slow
(“intentional”) movements from the faster (“unintentional”) tremors. The
control algorithm would then move the spoon to oppose the tremors.
RM: I agree with this; it’s a nice proposal.
BA: However, there does seem to be more to it: The system is said to be capable of being adjusted remotely to improve its performance. I imagine that this would involve retuning the filter to the specific tremor frequency of the individual using the spoon (in Parkinson’s, typically around 4 Hz). The
filter might even be a narrow-band pass filter that removes higher as well
as lower frequencies, thus allowing the spoon to “see” only the tremor
frequencies to which it is tuned and treat them as disturbances.
RM: Yes, a band pass filter would seem best ; the system wouldn’t waste energy opposing those very high (and low) frequency components of the tremor which are probably low amplitude anyway and don’t interfere that much with the accuracy with which the spoon gets to the mouth.
BA: I don’t see PCT as contributing anything to the spoon’s design, as the spoon already functions as a two-axis control system like those we use as models in PCT. It’s a nice control-system application.
RM: I agree that PCT can’t contribute to the spoon’s design, but for different reasons. I think the main contribution PCT could make is in providing an algorithm for distinguishing the intentional from the unintentional components of the movement of spoon to mouth. This would, of course, be the algorithm of the Test for the Controlled Variable, which is used to distinguish intentional from unintentional movements in my signature (and, apparently completely underwhelming) “Mind Reading” demo (http://www.mindreadings.com/ControlDemo/Mindread.html).
RM: But there are a couple of reasons why I think this method of distinguishing intentional from unintentional behavior would not work in this situation. First, the TCV algorithm takes a while to work (as you will see if you do the demo) and you need nearly instantaneous determination of the intended movement trajectory when lifting a spoon to your mouth to correct for disturbances to that trajectory; and second, the algorithm works best when control is good (which you can also see if you do the demo; the TCV not good at detecting the intentionally moved avatar – the controlled variable – until you get pretty good at moving the avatar against the prevailing disturbances) and the problem with hand tremor is that control of the movement trajectory is poor due to the instability of the control loop. So unless the Gyenno engine ers have found a way to overcome these limitations I’m pretty sure that they distinguish intentional from unintentional components of movement using the simple filtering process Bruce described.
Best
Rick
Bruce
-----Original Message-----
From: Warren Mansell [mailto:wmansell@gmail.com]
Sent: Friday, November 25, 2016 4:16 AM
To: csgnet@lists.illinois.edu csgnet@lists.illinois.edu; Control Systems
Group Network CSGNET@LISTSERV.ILLINOIS.EDU
Cc: Henry Yin hy43@duke.edu
Subject: Tremor spoonhttp://www.gyenno.com/spoon-en.html
Anyone know what algorithms and components these use - to cancel out
disturbances and ‘distinguish intentional movement’. Could PCT do any
better?
Warren
–
Richard S. Marken
“The childhood of the human race is far from over. We have a long way to go before most people will understand that what they do for others is just as important to their well-being as what they do for themselves.” – William T. Powers