Green Maja, Cabble Adam, Bailey Michael, Kappell Maria L, Billet Bart, Kim Choll W, Singh Jaspal R, Suthar Manish, Kalia Hemant, Kappell Shari, Chakravarthy Krishnan
Department of Pain Medicine, NXTSTIM Inc., San Diego, CA, USA.
Department of Neuroscience, Monash University, Clayton, Victoria, Australia.
J Pain Res. 2025 Aug 23;18:4337-4348. doi: 10.2147/JPR.S544476. eCollection 2025.
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.
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.
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.
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.
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.
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.
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.
慢性疼痛是全球致残的主要原因，传统药物治疗常常受到副作用、疗效不佳和成瘾风险的限制。非侵入性神经调节疗法，如经皮电刺激神经疗法（TENS）和电肌肉刺激疗法（EMS）提供了替代方案，但传统上受限于固定的刺激方案和用户参与度低。
评估EcoAI™的24个月现实世界有效性，这是一种由人工智能驱动的可穿戴系统，用于在社区环境中为慢性疼痛管理提供自适应TENS和EMS。
设计、设置和参与者：这项回顾性观察队列研究分析了2023年1月至2025年3月期间来自美国2135名成年用户的去识别数据。所有用户至少完成了一次治疗疗程，并通过移动应用程序提交了症状数据。
EcoAI通过经皮电刺激神经疗法（TENS）调节传入性疼痛信号，并通过电肌肉刺激疗法（EMS）改善局部循环和神经肌肉功能。一个嵌入式人工智能引擎根据用户报告的结果和生理指标动态调整刺激强度、波形和持续时间。
主要结局：自我报告的疼痛评分变化（0-10数字量表）。次要结局：情绪、身体功能、社交参与、工作活动和总体幸福感。还分析了疗程依从性和设备使用模式。
在187930次记录的疗程中，疼痛评分中位数从基线时的6.0降至6个月时的4.0和24个月时的3.0。在次要领域也观察到了具有统计学意义的改善（p<0.001）。每天进行2-4次、每次持续20-59分钟的疗程可取得最佳效果。老年人（≥60岁）表现出更高的参与度和疼痛缓解效果。未报告严重不良事件。
在这项回顾性分散研究中，EcoAI平台在慢性疼痛成人患者中显示出持续的多维度益处。这些发现支持了人工智能驱动的TENS/EMS作为药物治疗安全、可扩展和个性化辅助手段的潜力。
