e.g. mhealth
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Skip search results from other journals and go to results- 18 JMIR mHealth and uHealth
- 12 JMIR Formative Research
- 12 Journal of Medical Internet Research
- 5 JMIR Aging
- 5 JMIR Research Protocols
- 4 Iproceedings
- 4 JMIR Biomedical Engineering
- 3 JMIR Human Factors
- 3 JMIR Mental Health
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- 2 JMIR Medical Informatics
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- 1 Journal of Participatory Medicine
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Passive data collection methods refer to data captured automatically without participant effort (eg, sensors, metadata), whereas active methods require participant involvement (eg, completing surveys or assessments). Active data collection also requires input from the respondent in a manner that makes the goal of the research more apparent. On the other hand, passive assessment does not requiring respondent burden or input, but rather, relies on data that is collected continuously in the background.
JMIR Form Res 2025;9:e64082
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Influence of Pre-Existing Pain on the Body’s Response to External Pain Stimuli: Experimental Study
Before attaching the sensors to the fingers, the skin was cleaned with wet wipes, and GEL101 A was applied to the electrodes to improve conductivity, enhance signal quality, and reduce impedance. EMG data were acquired using the BIOPAC EMG Smart Amplifier, with three electrodes attached to the participant’s nondominant forearm. The skin in the sensor placement area was prepared by cleaning it with wet wipes, followed by abrasion and application of ELPREP.
JMIR Biomed Eng 2025;10:e70938
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Recently, the use of wearable inertial sensors for gait analysis has gained considerable traction [4-6]. Specifically, the daily step count serves as an indirect yet rather easily obtainable indicator of walking and physical activity [7].
JMIR Mhealth Uhealth 2025;13:e64213
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Traditional gait analysis methods are limited to fixed laboratory measurement environments, often using complex instruments such as single-camera image processing [24] and walking leap sensors [25] to record human gait motion, but they struggle to reflect real-world gait conditions. Moreover, nonwearable system equipment and testing are too expensive, making it difficult for people to measure related data on their own [26].
JMIR Form Res 2025;9:e58864
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The Fitbit Sense is equipped with a range of sensors, including a photoplethysmogram sensor, an optical heart rate sensor, an electrodermal activity sensor, an accelerometer, a gyroscope, and an ambient light sensor. The photoplethysmogram sensor uses green and red light-emitting diodes along with a photodiode to measure blood volume changes in the microvasculature of the skin, allowing for the estimation of heart rate and blood oxygen saturation.
JMIR Form Res 2025;9:e54630
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To organize the selected literature and facilitate a comprehensive analysis, a classification taxonomy was developed based on the types of sensors used for hydration monitoring in wearable technologies. This taxonomy categorized the papers into the following groups: electrical sensors, optical sensors, thermal sensors, microwave sensors, multimodal sensors, and commercial products (Figure 2).
JMIR Mhealth Uhealth 2025;13:e60569
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A suite of in-home monitoring sensors, developed at the Center to Stream Healthcare In-Place, and commercially licensed by Foresite Healthcare, LLC [14,15], were installed within the study participants’ homes. Data were collected from 3 types of in-home sensors: a bed mat containing 4 hydraulic transducers that captured ballistocardiogram signals, a thermal depth sensor for capturing gait and detecting falls, and passive infrared (PIR) motion sensors [16-19].
JMIR Mhealth Uhealth 2025;13:e56678
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Furthermore, the use of wearable or embedded sensors allows many different aspects of functional ability to be characterized and objectively quantified [12,13,17,18]. Thus, they provide more granular and more detailed information than captured with the single scores of traditional standard clinical assessments such as the Nine-Hole Peg Test, oral Symbol Digit Modalities Test, or the Timed 25-Foot Walk [19-21].
J Med Internet Res 2025;27:e63090
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The recent development of digital and wearable technologies has made it possible to continuously track PA in real life through sensors embedded in digital devices. This expansion provides researchers with a broader range of choices, as both research-grade and consumer-grade wearables, with varying costs and capacities to measure health conditions, are now available in the market.
J Med Internet Res 2025;27:e59878
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Toward Unsupervised Capacity Assessments for Gait in Neurorehabilitation: Validation Study
Moreover, combining the 10-MWT with wearable sensors, such as inertial measurement units, allows for the extraction of additional spatiotemporal gait parameters. These parameters are not only robust, but they enhance the interpretation of clinical assessment outcomes and aid in detecting motor recovery poststroke as well as predicting prognosis after stroke [24-26].
J Med Internet Res 2025;27:e66123
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