1. A service system for supporting ophthalmic surgical systems, the service system comprising:
a plurality of remotely located ophthalmic surgical machines;
a plurality of personal digital assistants; and
a central computer system communicatively coupled to each of the plurality of ophthalmic surgical machines and to each of the plurality of personal digital assistant, the central computer system configured to:
detect an operation fault of at least one of the plurality of ophthalmic surgical machines, the operation fault indicating a service requirement of the at least one of the plurality of ophthalmic surgical machines; and
notify at least one of the personal digital assistants of the operation fault.
2. The service system of claim 1, wherein the central computer system is configured to send software upgrades to any of the ophthalmic surgical machines upon receiving a request.
3. The service system of claim 1, wherein the plurality of ophthalmic surgical machines comprises one or more ophthalmic laser surgical machines, each of the one or more ophthalmic laser surgical machines configured to produce a total output energy amount during operation; and wherein the central computer system is further configured to:
monitor the total output energy amount of each of the one or more ophthalmic laser surgical machines; and
detect the operation fault when the total output energy amount of at least one of the one or more ophthalmic laser surgical machines exceeds a threshold energy level.
4. The service system of claim 3, wherein the central computer system comprises a database of profiles for each of the one or more ophthalmic laser surgical machines, the database of profiles based on at least one of the total output energy amount of each of the one or more ophthalmic laser surgical machines, a beam steering error, a coolant level error, a shutter error, a laser diode error, a galvo positioning error, a wavefront measurement, and a voltage measurement, and wherein the central computer system is further configured to predict the service requirement using the database of profiles.
5. The service system of claim 3, wherein the central computer system is further configured to:
determine a rate of change of the total output energy amount of each of the one or more ophthalmic laser surgical machines; and
detect the operation fault when the rate of change of the total output energy amount of at least one of the one or more ophthalmic laser surgical machines exceeds a threshold rate.
6. The service system of claim 1, wherein the plurality of ophthalmic surgical machines comprises one or more phacoemulsification- machines, each of the one or more phacoemulsification machines having a rotary vain pump, and wherein the central computer system is further configured to:
monitor a total usage of the rotary vain pump of each of the one or more phacoemulsification machines; and
detect the operation fault when the total usage of the rotary vain pump of at least one of the one or more phacoemulsification machines exceeds a threshold value.
7. The service system of claim 16 wherein the central computer system comprises a database of profiles for each of the one or more phacoemulsification machines, the database of profiles based on at least one of the total usage of the rotary vain pump of each of the one or more phacoemulsification machines, an amount of time for priming, a vacuum performance, a power performance, a power error, a temperature error, a computer error, a safety error, a footswitch error, an account warranty status, and a seriallot number, and wherein the central computer system is further configured to predict the service requirement using the database of profiles.
8. A method of servicing a plurality of surgical systems, the method comprising the steps of:
monitoring the plurality of surgical systems to obtain data indicating a status for each of the plurality of surgical systems;
determining an operation fault of at least one surgical system of the plurality of surgical systems based on the data and a database of pre-determined profiles corresponding to each of the plurality of surgical systems; and
notifying at least one technician of the operation fault.
9. The method of claim 8, wherein the step of notifying comprises identifying one or more technicians within a pre-determined proximity to the at least one surgical system.
10. The method of claim 8, wherein each of the at least one technician has a personal digital assistant, and wherein the step of notifying comprises transmitting an alert to the personal digital assistant of the at least one technician, the alert indicating the operation fault.
11. The method of claim 8, wherein the step of determining an operation fault comprises comparing the data with the database of pre-determined profiles to predict a service requirement of the at least one surgical system, the operation fault based on the service requirement.
12. The method of claim 8, wherein the at least one surgical system comprises a plurality of components, and wherein the step of determining an operation fault comprises predicting a service requirement of a first component of the plurality of components from the data.
13. The method of claim 8, wherein a first surgical system of the plurality of surgical systems comprises a database of operating conditions, each of the operating conditions acquired during an operation of the first surgical system, and wherein the step of monitoring comprises periodically accessing the database of operating conditions.
14. A support system for a plurality of remotely located ophthalmic surgical machines, the support system comprising:
a plurality of personal digital assistants; and
a central computer system communicatively coupled to each of the plurality of ophthalmic surgical machines and to each of the plurality of personal digital assistants, the central computer system configured to:
receive data from at least one of the plurality of ophthalmic surgical machines;
detect an operation fault of at least one of the plurality of ophthalmic surgical machines based on the data and a database on profiles corresponding to each of the plurality of ophthalmic surgical machines, the operation fault indicating a service requirement of the at least one of the plurality of ophthalmic surgical machines; and
transmit an alert to at least one of the personal digital assistants, the alert indicating the operation fault.
15. The ophthalmic surgical system of claim 14, wherein the central computer system is further programmed to send software upgrades to any of the ophthalmic surgical machines upon a request.
16. The ophthalmic surgical system of claim 14, wherein the plurality of remotely located ophthalmic surgical machines include one or more ophthalmic laser surgical machines, each producing an amount of total output energy during operation, and wherein the central computer system is configured to:
monitor the amount of total output energy of each of the one or more ophthalmic laser surgical machines; and
notify at least one of the personal digital assistants when the amount of total output energy of one or more ophthalmic laser surgical machines exceeds a threshold energy level.
17. The ophthalmic surgical system of claim 16, wherein the central computer system is further configured to:
calculate a rate of change of the amount of total output energy for each of the one or more ophthalmic laser surgical machines; and
notify at least one of the personal digital assistants when the rate of change of the amount of total output energy for one or more of the ophthalmic laser surgical machines exceeds a threshold rate.
18. The ophthalmic surgical system of claim 14, wherein one or more of the ophthalmic surgical machines are phacoemulsification machines each having a rotary vain pump, and wherein the central computer system is further configured to:
monitor a total usage of the rotary vain pump of each of the one or more phacoemulsification machines; and
notify at least one of the personal digital assistants when the total usage of one of the rotary vain pumps exceeds a threshold value.
19. The ophthalmic surgical system of claim 14, wherein the central computer system is further configured to compare the data with the database of profiles to predict the service requirement.
20. The ophthalmic surgical system of claim 14, wherein a first ophthalmic surgical machine comprises a plurality of components, wherein the central computer system is further configured to predict the service requirement of a first component of the plurality of components.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
What is claimed is:
1. A method of analyzing a distribution, comprising steps of:
(a) collecting data from a data source;
(b) constructing a histogram based on the data such that the histogram defines a distribution; and
(c) fitting tail regions of the distribution wherein deterministic and random components of the distribution are estimated.
2. The method of claim 1, wherein the fitting step comprises the steps of:
(a) finding a first and a second tail region of the distribution;
(b) fitting the first and second tail region to a predefined first model and second model, respectively; and
(c) estimating fitted parameters of the first model and the second model.
3. The method of claim 2, further comprising the step of checking the fitting of the first and second tail region.
4. The method of claim 2, further comprising the step of calculating the statistical confidence of the fitted parameters.
5. The method of claim 1, further comprising the step of displaying the deterministic and random components of the distribution.
6. The method of claim 2, wherein the finding step comprises the step of finding the fist and second tail region based on a first derivative and second derivative method.
7. The method of claim 2, wherein the first model and second model are Gaussian models.
8. The method of claim 2, wherein the first model and second model are multiple Gaussian models.
9. The method of claim 2, wherein the model parameters comprise and .
10. The method of claim 9, wherein the deterministic component is calculated according the following formula: 12.
11. The method of claim 10, wherein the random component is calculated according the following formula (12)2.
12. The method of claim 1, wherein the distribution comprises a signal distribution.
13. The method of claim 12, wherein the signal distribution is a jitter signal distribution.
14. An apparatus for analyzing a distribution, the apparatus comprising:
(a) a measurement apparatus for collecting data; and
(b) an analyzing unit, operatively connected to the measurement apparatus, for collecting data from the measurement apparatus, constructing a histogram based on the data such that the histogram defines a distribution, fitting tail regions of the distribution, wherein deterministic and random components of the distribution are estimated.
15. The apparatus of claim 14, wherein the analyzing unit further comprises:
(a) means for finding a first and a second tail region of the distribution;
(b) means for fitting the first and second tail region to a predefined first model and second model; and
(c) means for determining fitted parameters of the first model and the second model.
16. An article of manufacture comprising a program storage medium readable by a computer having a memory, the medium tangibly embodying one or more programs of instructions executable by the computer to perform method steps for performing operations analyzing a distribution, the method comprising the steps of:
(a) collecting data from a data source;
(b) constructing a histogram based on the data such that the histogram defines a distribution; and
(c) fitting tail regions of the distribution wherein deterministic and random components of the distribution are estimated.
17. The article of manufacture of claim 16, wherein the fitting step further comprises the steps of:
(a) finding a first and a second tail region of the distribution;
(b) fitting the first and second tail region to a predefined first model and second model; and
(c) determining the fitted parameters of the first model and the second model.