New technology opens new possibilities in the field of prevention and rehabilitation, both in research and in clinical practice. For example, wearable sensors such as accelerometers, gyroscopes and insole force inducers, are used for fall risk assessment [Citation1], for fall detection [Citation2,Citation3] and in rehabilitation programs [Citation4]. Furthermore, there is some evidence that virtual reality and video gaming may be a useful adjunct to stroke rehabilitation for the upper limb but there is insufficient evidence about the effect of those on balance and function [Citation5] or for hand dexterity and gait [Citation6]. However, affordable and feasible technology, e.g. from the video gaming industry and improved algorithms for image analyses of video recordings, allow for valid and reliable objective measurements of movement behaviour [Citation7]. These technologies open new possibilities for clinical assessments as well as feedback based training protocols, including specific methods for assessment of proprioception [Citation8]. Mobile health technology like smart phones and smart watches also offers new approaches for personalised interventions with feedback on own behaviour and has the potential to increase uptake of interventions and change behaviour over time [Citation9].
In our more and more stressful working life as practicing physiotherapist, it is of course tempting to adopt new technology that might have all the advantages mentioned above. However, to evidence-base clinical practice, all these new technologies need to be scrutinised in the same scientific way as all therapies and methods for measuring function, used in physiotherapy practice and as is done in science. Hence, technology need to be tested for validity and reliability in the same way as other methods for retrieving information in physiotherapy practice. Additionally, the effect of different interventions, including modern technology, must also be tested in a scientific way. Therefore, research including test for validity and reliability of new technology, as well as randomised controlled trials to measure the effect of interventions including technology, is highly demanded. One example of ongoing research in the effectiveness area, is a hip-rehabilitation project in Malmö, Sweden, where wearable mobility trackers are used as add-on in rehabilitation [Citation4]. The intervention in the randomised controlled trial comprises of structured rehabilitation with an Inertial Measurement Unit (IMU) called the Stumbelometer (www.infonomy.com) as an add-on the structured rehabilitation. The IMU collects data on time spent in sitting, standing, lying down and on steps per day, walking speed and step length. The physiotherapist gets specific knowledge about progression on function and can both give feedback to the patient and use the information for individualising exercises during rehabilitation.
As a researcher and a practicing physiotherapist, I urge all my colleagues to use your knowledge and skills of scientific methods and best available evidence when adopting technology in clinical practice. In that way, we can embrace and use new technology in rehabilitation and in research, that is effective, valid, and reliable.
References
- Pang I, Okubo Y, Sturnieks D, et al. Detection of near falls using wearable devices: a systematic review. J Geriatr Phys Ther. 2019 Jan/Mar;42(1):48–56. doi:10.1519/JPT.0000000000000181.
- Chander H, Burch RF, Talegaonkar P, et al. Wearable stretch sensors for human movement monitoring and fall detection in ergonomics. Int J Environ Res Public Health. 2020;17(10):3554.
- Schwickert L, Becker C, Lindemann U, et al. Fall detection with body-worn sensors: a systematic review. Z Gerontol Geriatr. 2013;46(8):706–719.
- Hansson EE, Fänge AM, Rogmark C. Assessing the outcome of rehabilitation after hip fracture with a wearable device-a study protocol for a randomized control trial in community healthcare. Int J Environ Res Public Health. 2021;18(19):10165.
- Laver KE, Lange B, George S, et al. Virtual reality for stroke rehabilitation. Cochrane Database Syst Rev. 2017;2018(1):CD008349.
- Rutkowski S, Kiper P, Cacciante L, et al. Use of virtual reality-based training in different fields of rehabilitation: a systematic review and meta-analysis. J Rehabil Med. 2020;52(11):1–16.
- Röijezon U, Faleij R, Karvelis P, et al. A new clinical test for sensorimotor function of the hand–development and preliminary validation. BMC Musculoskelet Disord. 2017;18(1):1–11.
- Clark NC, Röijezon U, Treleaven J. Proprioception in musculoskeletal rehabilitation. Part 2: clinical assessment and intervention. Man Ther. 2015;20(3):378–387.
- Helbostad JL, Vereijken B, Becker C, et al. Mobile health applications to promote active and healthy ageing. Sensors. 2017;17(3):622.