Book III–Connected Medical Devices–April 2015

Connected Medical Devices: Integrating Patient Care Data in Healthcare Systems. A new book by John Zaleski. This is my latest in the line of MDI texts, focused principally on the essentials of implementation. ... Read More

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Contributing Author–Dictionary of Computer Science, Engineering, and Technology

Zaleski, JR, (contributing Author), Dictionary of Computer Science, Engineering, and Technology, (CRC Press, Phil Laplante, Editor-in-Chief). ... Read More

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Book I–Integrating Device Data into the Electronic Medical Record

The seminal book on the medical device integration into health information technology systems. John Zaleski, Ph.D. A book on empirical practice of medical device interoperability, based on years of experience in the field. A Developer’s Guide to Design and a ... Read More

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Book II–Medical Device Data and Modeling for Clinical Decision Making

This work combines much of the experience learned in medical device interoperability and clinical informatics I have gained over the course of the past 20+ years. I have leveraged work from my  PhD and experience in product management of critical care. The devic... Read More

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PENN Dissertation ’96–Weaning from Postoperative Mechanical Ventilation

Modeling Post-Operative Respiratory State in Coronary Artery Bypass Graft Patients: A Method for Weaning Patients from Mechanical Ventilation. This PhD research developed a model for real-time assessment of patient postoperative recovery and viability for weaning f... Read More

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New Book 2015 | Connected medical devices



Connected Medical Devices: Integrating Patient Care Data in Healthcare Systems.

This is the latest in the line of books by John Zaleski on connected patient care devices. This text focuses on the practical aspects of implementing MDI in the hospital. Book contents are as follows:


  • The Mechanics of MDI;
  • Medical Device Driver Software;
  • The MDI Intermediary between the Medical Device and the Health IT system;
  •  Major MDI Solution Providers;
  • Vendor Agnostic Representation of MDI Solutions;
  • Some Tips on Selecting an MDI Solution; and,
  •  Chapter Summary.

Chapter 1: Medical Device Types and Classes Used in Hospital Departments and How They Communicate

  • Healthcare Enterprise Departments most often in need of MDI;
  • Medical Device Topologies;
  • Surgical Services Environments (Operating Room, OR; Post-Anesthesia Care Unit, PACU);
  • Essential OR Data Elements;
  • Parameter Transmission Intervals – OR;
  • Redundant Parameter Transmission;
  • Intensive Care Unit (ICUs) / Critical Care Units (CCUs);
  • Physiologic Monitors;
  •  Mechanical Ventilators;
  • Infusion Systems and Tourniquet Pumps;
  • Specialty Medical Devices;
  • Emergency Departments (EDs);
  • Medical Surgical / Step-Down Units;
  • Chapter Summary.

Chapter 2: MDI Solution Acquisition and Implementation

  • Starting the MDI acquisition process: build or buy
  • Building an MDI solution;
  • Acquiring an MDI solution;
  • The Request for Information (RFI) / Request for Proposal (RFP) Process;
  • Communicating Enterprise Requirements to MDI Solution Providers;
  •  Medical Device Driver Development & Timelines;
  • Communicating with the Health IT system;
  • Hospital Facilities and Enterprise Networking Requirements;
  • Building the MDI Implementation Team;
  • Project Management;
  • Staging the MDI Solution Implementation;
  • Assembling the MDI Implementation Team;
  • Estimating Timelines for MDI Implementation Completion;
  • Installation;
  • Testing;
  • Transition to go-live;
  • Chapter Summary.

Chapter 3: Semantic Data Alignment and Time Synchronization of Medical Devices

  • Interoperability Continuum;
  • Semantic Harmonization of Medical Device Data;
  • Temporal Alignment of Medical Device Data;
  • Validating Medical Device Data in the Health IT System Patient Chart;
  • Preparation for Go-Live Checklist; and,
  • Chapter Summary.

Chapter 4: Standards Surrounding Medical Device Integration to Health IT Systems

  • Medical Device Standards Specific to Medical Device Integration;
  • Health Level Seven (HL7) Standards Developing Organization;
  • IEEE 11073 Medical / Personal Health Device;
  • Health Level Seven (HL7) Observation Reporting;
  • Conditioning and Translating Connected Medical Device Data for IT System Consumption;
  • Patient Administration;
  • A Few Words About HL7 Fast Health Interoperable Resources;
  • Integrating the Healthcare Enterprise® (IHE);
  • Other Medical Device Integration-Related Standards; and,
  • Chapter Summary.

Chapter 5: Notification, Alerts & Clinical Uses of Medical Device Data

  • Interface Health and Status Notification and Technical Alerts;
  • Clinical Alerts and Notifications;
  • Aperiodic versus Periodic Data Collection;
  • Clinical Uses of Medical Device Data; and,
  • Chapter Summary.

Chapter 6: Patient Identification and Medical Device Association

  • Methods for Patient Identification;
  • Barcode and RFID;
  • Medical Device Association Workflows;
  • Chapter Summary.

Chapter 7: Regulatory and Security Considerations of MDI

  • Medical Device Data Systems (MDDS);
  • Regulatory Classification and Identification of Risk;
  • Medical Device Security;
  • IEC 80001;
  • Software Development Methodologies and Testing;
  • Chapter Summary.

Appendix A.1: Medical Device Quantity Planning Table

Appendix A.2: Testing Tools

Appendix A.3: HL7 Testing Simulator

Book Cover - Zaleski

Book III Cover



Kalman Filtering Using Microsoft Excel | Kalman Filter



This post is dedicated in response to those who have contacted me expressing interest in various mathematical models for Kalman filtering I have developed over the years.

The following link provides an example of the Kalman filtering application. Hence, I will not go into the theory here: Signal artifact smoothing using the EKF…

An MS Excel model has been created for tracking blood glucose. An image of the spreadsheet is provided below:

Screenshot 2015-02-09 16.44.28











Spinner buttons are used to provide for the adjustment of process noise (qk) and measurement noise (vk). The following screen shots show various levels of measurement noise on the tracked overlay on the original signal.

The following plot shows vk = 0; the one following, vk = 0.05.

Any interest in obtaining the actual spreadsheet, please send me an email at

Screenshot 2015-02-09 16.48.05

No measurement noise

Screenshot 2015-02-09 16.48.24

vk = 0.05


Haar Wavelets in Microsoft Excel



By John R. Zaleski

Recently, I received a comment from a reader on Disqus on an older posting regarding Haar Wavelet Transforms. This reader requested that I post an example of the MS Excel file that actually creates a Haar basis function and performs the transformation.

In the example, I include a set of 8 (x,y) pairs, which are then transformed using a Haar wavelet to their basis coefficients. The plot below illustrates the random data points.


Raw (x,y) data points

Lossy signal reconstruction: all basis function values < 2 removed.

Lossy signal reconstruction: all basis function values < 2 removed.

The MS Excel spreadsheet, which I show below, is used to create the basis coefficients and the inverse Haar matrix. A threshold spinner button was added to allow for removing basis coefficients experimentally to see the effect on the recreated signal when certain coefficients are removed from the calculation. This has the effect of “lossy compression”, illustrating quite nicely the effect on recreating an imperfect reproduction of the original signal.

Note: if you would like a copy of the spreadsheet, please contact me through email at

DWT Discrete Wavelet Transform in Microsoft Excel



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