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Phantom motor execution facilitated by machine learning and augmented reality as treatment for phantom limb pain: a single group, clinical trial in patients with chronic intractable phantom limb pain
Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden; Centre for Advanced Reconstruction of Extremities, Sahlgrenska University Hospital, Mölndal, Sweden; Integrum AB, Mölndal, Sweden.
Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden; Integrum AB, Mölndal, Sweden.
Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden; Integrum AB, Mölndal, Sweden.
Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden; Integrum AB, Mölndal, Sweden.
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2016 (English)In: The Lancet, ISSN 0140-6736, E-ISSN 1474-547X, Vol. 388, no 10062, 2885-2894 p.Article in journal (Refereed) Published
Abstract [en]

Background: Phantom limb pain is a debilitating condition for which no eff ective treatment has been found. We hypothesised that re-engagement of central and peripheral circuitry involved in motor execution could reduce phantom limb pain via competitive plasticity and reversal of cortical reorganisation.

Methods: Patients with upper limb amputation and known chronic intractable phantom limb pain were recruited at three clinics in Sweden and one in Slovenia. Patients received 12 sessions of phantom motor execution using machine learning, augmented and virtual reality, and serious gaming. Changes in intensity, frequency, duration, quality, and intrusion of phantom limb pain were assessed by the use of the numeric rating scale, the pain rating index, the weighted pain distribution scale, and a study-specifi c frequency scale before each session and at follow-up interviews 1, 3, and 6 months after the last session. Changes in medication and prostheses were also monitored. Results are reported using descriptive statistics and analysed by non-parametric tests. The trial is registered at ClinicalTrials. gov, number NCT02281539.

Findings: Between Sept 15, 2014, and April 10, 2015, 14 patients with intractable chronic phantom limb pain, for whom conventional treatments failed, were enrolled. After 12 sessions, patients showed statistically and clinically signifi cant improvements in all metrics of phantom limb pain. Phantom limb pain decreased from pre-treatment to the last treatment session by 47% (SD 39; absolute mean change 1 . 0 [0 . 8]; p= 0 . 001) for weighted pain distribution, 32% (38; absolute mean change 1 . 6 [1 . 8]; p= 0 . 007) for the numeric rating scale, and 51% (33; absolute mean change 9 . 6 [8 . 1]; p= 0 . 0001) for the pain rating index. The numeric rating scale score for intrusion of phantom limb pain in activities of daily living and sleep was reduced by 43% (SD 37; absolute mean change 2 . 4 [2 . 3]; p= 0 . 004) and 61% (39; absolute mean change 2 . 3 [1 . 8]; p= 0 . 001), respectively. Two of four patients who were on medication reduced their intake by 81% (absolute reduction 1300 mg, gabapentin) and 33% (absolute reduction 75 mg, pregabalin). Improvements remained 6 months after the last treatment.

Interpretation: Our fi ndings suggest potential value in motor execution of the phantom limb as a treatment for phantom limb pain. Promotion of phantom motor execution aided by machine learning, augmented and virtual reality, and gaming is a non-invasive, non-pharmacological, and engaging treatment with no identifi ed side-eff ects at present.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 388, no 10062, 2885-2894 p.
National Category
Family Medicine
Identifiers
URN: urn:nbn:se:oru:diva-54312DOI: 10.1016/S0140-6736(16)31598-7ISI: 000389631700033Scopus ID: 2-s2.0-85003707590OAI: oai:DiVA.org:oru-54312DiVA: diva2:1063417
Funder
VINNOVA
Note

Funding Agencies:

Promobilia Foundation

Jimmy Dahlstens Fond

PicoSolve

Innovationskontor Väst

Available from: 2017-01-10 Created: 2017-01-09 Last updated: 2017-01-10Bibliographically approved

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CiteExportLink to record
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