Pain Trajectory Curves
Pain Trajectory Curves - Related Videos
01:26
Orthogonal Trajectories
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2026
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
16:14
Trajectory Data Analyses for Pedestrian Space-time Activity Study
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Cited by 15 •
2013
A suite of spatiotemporal processing methods are presented to analyze human trajectory data, such as that collected using a GPS device, for the purpose of modeling pedestrian space-time activities.
04:24
Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns
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Cited by 3 •
2011
We describe a protocol to observe and analyze cell rolling trajectories on asymmetric receptor-patterned substrates. The resulting data are useful for engineering of receptor-patterned substrates for label-free cell separation and analysis.
11:46
Urinary Bladder Distention Evoked Visceromotor Responses as a Model for Bladder Pain in Mice
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Cited by 19 •
2014
Approximately 3-8 million people in the United States suffer from interstitial cystitis/bladder pain syndrome (IC/BPS), a debilitating condition characterized in part by pelvic pain. In order to study nervous system contributions to the condition, a physiological model of urinary bladder pain is used in mice and rats.
09:38
Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery
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Cited by 17 •
2016
Human pain models are valuable tools used to assess the analgesic potential of novel compounds and predict their clinical efficacy, especially when used in an integrated manner. Although implementation of these models is complex, with proper execution, the pain models described in this protocol can provide predictive and reliable results.
FAQs
They organize repeated observations into recognizable courses, including rapid improvement, persistent pain, delayed resolution, and worsening symptoms. This pattern-based view helps separate patients who improve quickly from those whose symptoms remain or intensify over time. In clinical research, the resulting categories support more precise descriptions of recovery and disease progression than a single assessment.
A curve may follow pain intensity, pain frequency, or pain interference, depending on the clinical or research question. Intensity describes how severe the pain is, frequency reflects how often it occurs, and interference captures its effect on daily functioning. Selecting the relevant dimension allows analysis to focus on the outcome most important to patient care or study goals.
Repeated patient-reported outcomes provide the observations needed to examine change across time rather than only describing pain at one moment. Longitudinal analysis then identifies whether symptoms improve rapidly, resolve later, persist, or worsen. This timing information is important when studying recovery, disease progression, or the transition from acute pain toward persistent pain.
Clinicians can use observed pain patterns to support prognosis and identify patients who may be at risk for chronic pain. A course showing persistent, delayed, or worsening symptoms can signal a different outlook from rapid improvement. These patterns help inform patient-centered care by showing how an individual’s recovery is unfolding over time.
Researchers can track changes after surgery, medication, rehabilitation, or other interventions and examine whether pain improves, persists, or worsens. Curves also allow treatment groups to be compared across time, rather than relying only on an endpoint. This approach helps evaluate responses to care and clarifies whether an intervention is associated with a particular recovery pattern.
Pain trajectory curves help investigators study factors that influence whether acute pain resolves or becomes persistent. They can also characterize disease progression, compare recovery patterns between treatment groups, and examine patient-reported outcomes over time. In medicine, these analyses connect symptom change with prognosis and support efforts to refine treatment decisions and patient-centered care.