Headache and Digital Health: The Future of Headache Medicine

The integration of technology and medicine provides an exciting platform for the future of headache medicine. Migraine afflicts a large portion of the worldwide population, and the number of specialists trained in headache medicine is limited; therefore, there is a great need for technology to aid in the diagnosis, treatment, and prevention of migraine. Migraine is unique in that diagnosis is typically based on clinical history and lived experience; thus, there is an opportunity for technology to aid headache specialists in case management. Substantial research has been published in the past decade aimed at expanding the use of technology to help individuals and providers access tools for the timely diagnosis and treatment of headaches. Further growth in this area is both predicted and needed. Technology will complement the acceleration of migraine treatment, enhance overall quality of life for people with headache, and improve access to care. We provide a broad overview of how technology is being used in headache medicine.

Diagnosing Headache Using Online Platforms

The use of digital tools in headache medicine began in the 1960s, marked by initial successes in classifying headache types and progressing into the 1970s to include self-administered questionnaires. The adoption of these early tools was hampered by inconsistent classification systems and limited computer access. The early 2000s witnessed accelerated development, with innovations such as the AIDA Cefalee computer-assisted diagnosis database for headache management and the Computerized Headache Assessment Tool, although these were bound by the criteria of their time.¹ A major milestone was reached in 2014 with the launch of a clinical decision support system aligned with the International Classification of Headache Disorders, 3rd edition (ICHD-3) standards that aimed to mirror the precision of headache specialists in primary care.²

The diagnostic criteria guiding the development of digital tools for headache diagnosis have varied, while predominantly following the ICHD-3 framework.³ The tools have been deployed using a range of methods, from face-to-face and telephone interviews to questionnaire-based assessments. Some of these digital instruments achieved perfect scores in key diagnostic accuracy measures—sensitivity, specificity, and concordance.³ Some are specifically designed for migraine detection, using a binary approach, categorizing conditions as either migraine or not migraine;⁴ others offer a more comprehensive diagnosis, distinguishing among migraine, tension-type headache, trigeminal autonomic cephalgias, and other types of headache.⁴

The past 5 years have witnessed a surge in advanced algorithmic tools worldwide, harnessing machine learning to deliver increasingly accurate diagnoses. Dutch, German, Iranian, Serbian, Turkish, and US researchers have evaluated different diagnostic algorithms, achieving accuracy rates ranging from 65% to 100%.³ The push for digital health solutions has been accelerated by the COVID-19 pandemic. This timeline of innovation not only reveals the enormous improvements in headache diagnostic tools over time but also highlights the evolving intersection of technology and health care; the potential for scalability and personalization continues to grow.

The Identify Chronic Migraine (ID-CM) screener is a 6-item questionnaire specifically developed to identify chronic migraine, an often undertreated and underdiagnosed condition. The classifications of ID-CM administered online and by physical mail and physician-led semi-structured interview (SSI) were compared to evaluate sensitivity and specificity of this screening tool. Using the SSI as the diagnostic standard, the ID-CM had a sensitivity of 70.8% and a specificity of 93.2%. The results of this study also support the real-world utility of the ID-CM as a simple and useful tool to identify individuals with chronic migraine.

The Penn Online Evaluation of Migraine (POEM) represents another advancement in digital headache diagnostics.⁶ This online questionnaire uses branching logic to collect standardized headache histories. An automated algorithm analyzes the responses, categorizing participants according to ICHD-3 criteria. POEM was tested on a cohort of adults (mean age, 41 years) previously evaluated by a neurologist. POEM demonstrated 83% sensitivity and 90% specificity for correctly identifying migraine cases compared with previous determinations made through neurologist interviews. Another online tool—BonTriage, a publicly available website—allows individuals to enter their headache data and create a report to show their physicians, permitting synergy between the online platform and human clinical practice.⁷

Practicing Headache Medicine With Telehealth

Telehealth leverages digital communication and information technology to enrich various aspects of health care delivery, encompassing diagnosis, treatment, education, and administrative processes. Teleneurology has emerged as a viable option for headache management, offering both health care providers and individuals more avenues for care and efficient information sharing, while overcoming geographic barriers.⁸ Teleconsultation is a component of teleneurology that involves the use of telecommunications, such as online video calls, to carry out medical consultations. This digital approach is proving effective in managing headache-related conditions with outcomes that often mirror those of in-person visits, achieving similar reductions in headache severity and frequency.⁸ For people with migraine, both avenues are similarly successful in decreasing scores on the Migraine Disability Assessment Scale.⁸ Teleconsultation has become a powerful tool for improving health care efficiency, reducing the average time spent per clinical visit.⁸ Its convenience opens access to a broad range of specialists and skilled providers who might not be available locally.

In addition, individuals have the opportunity to participate in virtual therapies and activities, such as exercise classes, guided meditation, and psychotherapy sessions conducted from home. Among individuals with headaches, meditation and mindfulness applications, along with online psychotherapy, stand out as popular and effective forms of complementary therapy.⁹ Teleneurology has opened up a wealth of options for managing headaches, allowing for greater flexibility and reach.¹⁰

Mobile Health Applications

There are many commercially available mobile health applications for headache management.¹¹ User-friendly applications can record important headache characteristics, including triggers, patterns, and successful treatments, to create a customized experience.¹¹ Studies involving the use of apps have also shown promising results in preventing migraine attacks by integrating behavioral therapy. One study showed that participants who used a progressive muscle relaxation app (RELAXaHead; Irody, Boston, MA) had clinically significant outcomes if they used the app at least twice weekly.¹² The convenience of accessing this evidence-based therapy through an app, which users can access at any time without incurring costs associated with health care visits, offers a practical option for individuals seeking accessible care.

Some people use apps to help identify headache triggers. However, significant correlations have not been identified. The difficulty in accurately identifying and statistically validating individual migraine triggers in mobile health apps represents a limitation of these tools. In a 90-day study of migraine triggers, participants tracked daily data, and identified an average of 28 triggers that were significant contributors to their migraine attacks.¹³ However, only 2 triggers per person were linked to a higher risk of migraine. Even the most frequently suspected triggers, such as sleep quality, stress, and dehydration, were found to be statistically significant in fewer than a third of individuals. There remains opportunity for future research and innovation to develop technology that can achieve this level of customization.

Wearables

Emerging digital tools, such as wearable sensors that sync with smartphones, are opening up new avenues in headache practice. One approach involves biofeedback, which uses instant feedback from autonomic bodily processes—changes in heart rate from breathing, activity, or emotions—to help people become more attuned to their body’s signals. Heart rate variability (HRV) biofeedback, a technique involving tracking and responding to HRV, is gaining ground in migraine care. A study including 52 participants using the HeartMath Inner Balance Sensor comparing an HRV biofeedback group with a control group found that although the main outcomes were similar across groups, participants who used the app/wearable more frequently saw greater benefits.¹⁴ This indicates that consistent use of HRV biofeedback might enhance treatment efficacy, although the study did not show a significant improvement in quality of life for those with migraine when compared with the waitlist control group.

Recent trials have explored the feasibility and usability of new biofeedback therapy applications paired with wearables. In one study, 18 adults with migraine used a smartphone app connected to wearable sensors for a 4-week trial.¹⁵ The Cerebri app from Nordic Brain Tech offered biofeedback training and a headache diary. Participants used 2 sensors to measure surface electromyographic voltage at the trapezius muscle, heart rate at the second fingertip, and skin temperature at the fingertip. They completed daily diary entries and 10-minute biofeedback sessions. After the test period, the participants’ feedback was largely positive, although there were some suggestions for design improvements for both the wearable and the app. The study confirmed that the intervention is safe and well-tolerated, laying a promising foundation for future efficacy studies. Other commercially available wearables, such as Juva,¹⁶ have not yet been studied in clinical trials but are being used in clinical practice.

Artificial Intelligence

Beyond the advancements in digital health aimed at improving the management of headache medications, the application of artificial intelligence (AI) is emerging. AI combines algorithms with machine learning (ML) techniques to allow adaptation, permitting it to make decisions and carry out tasks autonomously.¹⁷ AI has been used in several areas of neurology. One of AI’s earliest uses in neurology was using algorithms to diagnose stroke on CT imaging.¹⁸ ML has also shown promising results in detecting seizure activity on EEG recordings.¹⁹

AI has several applications in headache medicine. One of the most noteworthy was the development of a Computer-based Diagnostic Engine (CDE) designed to diagnose migraine.²⁰ The engine involves a rule set derived from the ICHD-3 criteria for primary headaches, as well as assessing for secondary headaches and medication overuse headache. ML may reduce the number of questions needed to be asked to reach a diagnosis. Users can bring this information for further discussion with their practitioner. Thus, ML may also create a more coherent and conversational experience.

To assess the accuracy of the CDE, participants were randomly allocated to 1 of 2 sequences: first experiencing the CDE and then engaging in an SSI with a headache specialist (using the same ICHD-3 criteria), or starting with the SSI followed by the CDE. There was almost perfect concordance in the diagnosis of migraine and probable migraine between the CDE and SSI (κ=.82 [95% CI, .74 to .90]). The CDE demonstrated a diagnostic accuracy of 91.6% (95% CI, 86.9%–95.0%), a sensitivity rate of 89.0% (95% CI, 82.5% to 93.7%), and a specificity rate of 97.0% (95% CI, 89.5% to 99.6%).²⁰

Katsuki et al²¹ developed an AI model designed to assist nonheadache specialists with headache diagnoses. This model assessed 17 variables and was trained to predict 1 of 5 diagnoses. This rule set was trained on data from 2800 individuals, then further tested and refined on data from 1200 individuals. Two groups of nonheadache specialists then saw 50 individuals: 1 group alone, and the other assisted by the AI model. The group without AI support had an overall accuracy of 46% (κ=.21); the group with AI support had an overall accuracy of 83.2% (κ=.68).

In addition to AI models used to aid in diagnosing migraine, AI has been used to assess migraine comorbidities. Attia et al²² developed an AI-powered ECG algorithm by using a convolutional neural network (CNN) that assessed 8 independent leads from a standard 12-lead ECG. The CNN was trained, with deep learning, to identify atrial fibrillation (AF). Chiang et al²³ applied this CNN to ECGs of individuals with migraine with and without aura. The algorithm demonstrated a greater AF prediction model in those with migraine with aura than in those with migraine without aura (mean [SD], 7.3% [15.0%] vs 5.6% [12.4%], respectively; mean difference [95% CI], 1.7% [1.5% to 2.0%]; P<.001). This finding suggests that migraine with aura may be an independent risk factor for AF.

Most recently, a natural language processing algorithm that can accurately determine headache frequency from free-text clinical notes was released into GitHub. The goal of this natural language processing algorithm is to help determine the appropriate level of headache care needed for individuals based on headache frequency, introducing another interesting use of AI for headache management.²⁴

Conclusion

The integration of innovative technologies into headache medicine is marking the start of a new and dynamic phase where digital resources, telehealth services, mobile applications, wearable devices, and AI are becoming fundamental elements to enhance patient care and lead to better health outcomes. The advent of digital technology in headache practice is an essential development against the backdrop of the global migraine burden and the scarcity of specialists. These complementary tools enable the personalization of treatment strategies, leading us toward an era where care may be more accessible, efficient, and person-centered.