Real-World Effectiveness of a Novel AI-Software Dependent Neuromodulation (ASDN) with Remote Monitoring Capability Field Stimulation Device for Chronic Pain: A 24-Month Analysis of Over 2000 Patients
Maja Green,1 Adam Cabble,1 Michael Bailey,2 Maria L Kappell,1 Bart Billet,3 Choll W Kim,4 Jaspal R Singh,5 Manish Suthar,6 Hemant Kalia,7 Shari Kappell,1 Krishnan Chakravarthy1 1Department of Pain Medicine, NXTSTIM Inc., San Diego, CA, USA; 2Department of Neuroscience, Monash University, Clayton, Vi...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Dove Medical Press
2025-08-01
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| Series: | Journal of Pain Research |
| Subjects: | |
| Online Access: | https://www.dovepress.com/real-world-effectiveness-of-a-novel-ai-software-dependent-neuromodulat-peer-reviewed-fulltext-article-JPR |
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| Summary: | Maja Green,1 Adam Cabble,1 Michael Bailey,2 Maria L Kappell,1 Bart Billet,3 Choll W Kim,4 Jaspal R Singh,5 Manish Suthar,6 Hemant Kalia,7 Shari Kappell,1 Krishnan Chakravarthy1 1Department of Pain Medicine, NXTSTIM Inc., San Diego, CA, USA; 2Department of Neuroscience, Monash University, Clayton, Victoria, Australia; 3Department of Anaesthesiology, AZ Delta Hospital, Roeselare, Belgium; 4Department of Orthopaedic Surgery, Scripps Memorial Hospital, La Jolla, CA, USA; 5Center for Global Health, Weill Cornell Medicine, New York, NY, USA; 6Pain Prevention and Rehabilitation Center, Chesterfield, MO, USA; 7Department of Pain Medicine, Invision Health, Rochester, NY, USACorrespondence: Maja Green, Department of Pain Medicine, NXTSTIM Inc., 5362 Sweetwater Trails, San Diego, CA, 92130, USA, Tel +1 858 910-1778, Email mgreen@nxtstim.comImportance: Chronic pain is a leading cause of disability worldwide, and conventional pharmacologic treatments are often limited by side effects, inadequate efficacy, and risk of dependency. Non-invasive neuromodulation therapies such as TENS and EMS offer alternatives but are traditionally constrained by fixed stimulation protocols and low user engagement.Objective: To evaluate the 24-month real-world effectiveness of EcoAI™, an AI-driven wearable system delivering adaptive TENS and EMS for chronic pain management in community settings.Design, Setting, and participants: This retrospective observational cohort study analyzed de-identified data from 2135 adult users across the United States between January 2023 and March 2025. All users completed at least one therapy session and submitted symptom data via a mobile application.Intervention: EcoAI delivers transcutaneous electrical nerve stimulation (TENS) to modulate afferent pain signaling and electrical muscle stimulation (EMS) to improve local circulation and neuromuscular function. An embedded AI engine dynamically adjusts stimulation intensity, waveform, and duration based on user-reported outcomes and physiological markers.Main Outcomes and Measures: Primary outcome: change in self-reported pain score (0– 10 numeric scale). Secondary outcomes: mood, physical function, social engagement, work activity, and overall well-being. Session adherence and device usage patterns were also analyzed.Results: Across 187,930 recorded sessions, median pain scores declined from 6.0 at baseline to 4.0 at 6 months and 3.0 at 24 months. Statistically significant improvements (p < 0.001) were also observed in secondary domains. Optimal outcomes were achieved with 2– 4 sessions per day lasting 20– 59 minutes. Older adults (≥ 60 years) demonstrated greater engagement and pain relief. No serious adverse events were reported.Conclusions and Relevance: In this retrospective, decentralized study, the EcoAI platform demonstrated sustained, multidimensional benefit in adults with chronic pain. These findings support the potential of AI-driven TENS/EMS as a safe, scalable, and personalized adjunct to pharmacologic care.Keywords: chronic pain, transcutaneous electrical nerve stimulation, TENS, electrical muscle stimulation, EMS, field stimulation, remote therapy monitoring, remote patient monitoring, artificial intelligence, digital therapeutics, real-world evidence |
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| ISSN: | 1178-7090 |