There’s a subtle but critical difference between wireless network engineers, who possess deep knowledge of both wireless and networking concepts, and network engineers who view wireless as just another networking technology.
Velaspan’s founders and many of our senior technical resources are the former. We came of age with RF, understand wireless’s physical layer, and take an RF-first approach. We use tools but ultimately rely on intuition. This has proven to be Velaspan’s competitive edge, and the difference between us and most IT solution providers.
So when one of our partners asked us to help their client with a non-WiFi wireless issue, we jumped at the chance to crack an RF-specific case – and to solve an urgent healthcare problem in the process.
THE CHALLENGE
Our partner’s client is a Miami hospital that, like most, uses a telemetry system connected wirelessly to patient-wearable EKG sensors that transmit the encoded electrical activity of patients’ hearts to real-time monitoring stations.
Alarmingly, the telemetry system was experiencing occasional but extreme interference. There was no apparent rhyme nor reason for the interruption. EKG sensors lost connectivity randomly amidst a variety of circumstances, making the problem impossible to reproduce on demand. Hospital leadership initially suspected patient TVs were the issue. They’d gone as far as replacing them – to no avail. Now they faced an urgent and daunting task: Identifying which of the hundreds of systems and variables inside and outside of their facility was the interference source.
Velaspan sent engineer Andrew Seger to Miami to get to the heart of the matter.
DIAGNOSIS SOUGHT
This hospital’s particular telemetry system transmits data over a proprietary network that uses a few specific frequency bands including 600 MHz – the band being encroached upon and therefore Andrew’s focus.
On his first trip, Andrew used a spectrum analyzer to identify and assess the breadth and depth of the overall RF environment in an attempt to identify RF interference: How significant was it? Was it coming from inside or outside of the hospital? Most importantly, could it be tied to a reported interference event?
Because no reported interference occurred while Andrew was measuring RF, the assessment’s potency was limited. He would come to realize why – but we’re getting ahead of ourselves. Andrew nonetheless gathered key clues as to what might be happening. Returning to Pennsylvania, he reviewed his findings and began homing in on possible interference sources.
He deduced that the interference was, in fact, coming from inside the hospital. There was even a chance that the issue was with the telemetry system itself.
He presented his hypotheses and proposed next steps to Velaspan’s partner and to hospital administrators, who asked him to fly back to Miami to test his emerging theories.
Even if interference did occur on this second visit, diagnosis would be still challenging. All RF energy at a given frequency, whether signal or interference (also called noise), looks the same on a spectrum analyzer, making it impossible to readily distinguish between the two. One can only be identified in the absence of the other, and vice versa. To identify interference sources, then, engineers typically power off or otherwise remove signal sources one by one, or move around a space, watching signals rise and fall and drawing conclusions accordingly. However, this proves difficult in healthcare settings, for two reasons:
For one, a vast number of confirmed and possible RF-emitting technologies exist and operate simultaneously in hospitals, making isolation difficult. Many are critical – life support, communication systems, and related monitors, for example. They cannot be silenced for signal isolation because lives are on the line.
Even more, in this particular hospital every telemetry system antenna facility-wide connects back to a central monitoring system that aggregates all signals. Within the telemetry system, interference present in one area of the hospital could impact an EKG sensor’s data in a completely different area. Interference identification is therefore akin to listening for a faucet drip at the Super Bowl: It’s nearly impossible to distinguish and there’s no getting around competing noise. Another analogy: It’s like searching for a needle in multiple haystacks, except messing with the hay jeopardizes patient wellbeing.
Andrew was joined on his second visit by a technical representative of the affected telemetry system and a representative of a nurse call system that Velaspan suspected might be the interference source.
He started by ruling out the telemetry system as the problem. The system comes from a leading manufacturer whose products are used in many hospitals where Velaspan works. No one was surprised when Andrew concluded that it was operating as designed.
Next, Andrew fixed his sights on nurse call system indicator lights – fixtures in hallways outside of each room that illuminate when a patient requires assistance. At face value, these wired lights were unlikely culprits. However, non-wireless systems can, in fact, produce interference by creating energy that isn’t engineered signal but rather noise that is a by-product of its normal operation.
Sure enough, when one of the lights was momentarily disconnected by the manufacturer’s technician, a small slice of energy measured by the spectrum analyzer disappeared – and returned when the light was reenergized. Some circuit-level component of the light fixture (likely an oscillator) was generating unwanted energy in the same small, licensed part of the broad 600 MHz spectrum used by the telemetry system.
Ultimately, examples of the condition were detected on at least twenty light fixtures, with a good chance of more hiding out behind the signal, awaiting discovery. The strength of the interference (and, ultimately, its impact) positively correlated to a light’s distance from the antenna. Lights outside of patient rooms closest to the antenna were the worst offenders. Because RF noise from each light was relatively quiet, though, it only interfered with telemetry sensors when signals were weak, i.e. when EKG sensors were further away from the system’s receive antennas, like when a patient walked down the hall. This explained why the interference was sporadic, temporary, and relatively rare. To absolutely confirm the cause-and-effect, Andrew donned an EKG wearable operating at the same frequency as the interference and observed the interference (error) event on the system monitor.
While inspecting the lights with the nurse call system representative, Andrew also observed that the wired indicator lights weren’t properly grounded, potentially contributing to the issue.
OUTCOME
With the interference source identified by Velaspan, the hardest part was done. However, the hospital now faced another challenge: choosing from remediation options.
Velaspan’s suggestions were two-fold: move antennas further away from the lights to reduce their impact on the telemetry system monitors and encourage the nurse call system manufacturer to add grounding and/or RF shielding into its devices in efforts to reduce or completely eliminate the interfering energy source.
This engagement – Velaspan’s version of a high-stakes race against the clock – brought us back to our roots, and to our core competency: RF. It’s expertise that has a bearing on all things cellular and Wi-Fi and puts Velaspan a step ahead of the rest.
Are you ready to solve your toughest wireless challenges with confidence?
Let’s Discuss