## 4 Discussion
Technology acceptance has only been minimally explored in the literature to date, though much rich data describing stroke survivor experiences are available [8; 41; 42]. It was feasible to set up and run three- to four-hour recording sessions during the participant's routine clinical care in both acute and inpatient environments with minimal to no interference in routine care. A structured inpatient rehabilitation schedule made it easier to apply the sensors and capture therapeutic activities, compared to acute care scheduling that often varied based on therapist availability and medical procedures. The variability in schedule and different therapeutic activities may have impacted sEMG outcomes. However, it is advantageous to use sEMG to record and track this variability as it may more accurately reflect typical trajectories of arm use and motor control during recovery [43]. What is less clear is whether this type of sEMG monitoring can be reliably conducted in home environments by stroke survivors and their caregivers. However, a researcher or clinician scientist could incorporate training sessions at home to ensure that sensors were reliably placed, in addition to using methods such as temporary tattoos or a fabric sleeve with pre-measured sensor cutouts for individuals to achieve consistency. This type of training would be essential to maximize the clinical utility of in-home sEMG monitoring. There were several limitations to this study. First, there was a lack of consistent quantitative data in [PERSON]'s electronic medical record that described functional recovery. The available data were reported and compared with sEMG output. Despite purposefully selecting the Biostamp sensors for their technical features among many other systems previously researched by this study team, there were also limitations in the sEMG sensors themselves, pointing to important needs for future development and research [28; 29]. Whilethe design of the sensors was comfortable and unobtrusive to the participant, the size of the sensors may have allowed for cross talk between muscles and decreased the quality of the signal. Recordings were affected by occasional failure of the double-sided stickers provided by the manufacturer, especially when the participant was sweating. Similarly, the participant's changing skin conditions, hydration, and ambient environmental conditions likely influenced skin impedance and data quality, limiting comparisons of absolute sEMG magnitude between days. The hardware also had several limitations. At high sampling rates (1000 Hz), the Biostamp sensors have a noise signal with a frequency of approximately 8.2 Hz which made the analysis of contractions of less than 100 MS impossible. Similarly, while longer periods of monitoring would have been ideal, the data storage capacity and upload time limited the length and frequency of collection. Changes in the participant's upper extremity muscle tone throughout the duration of the study may have impacted the consistency of sensor placement by the researcher, although SENIAM placement guidelines were followed by the same researcher at each visit to maximize consistency [44]. While [PERSON] was quite motivated throughout his recovery and demonstrated significant functional return, his recovery process may not be representative of a typical stroke survivor, and must be considered only as a distinct experience of individual recovery. However, this does not diminish the applicability of the study procedures and proof-of-concept for sEMG use in hospital settings for other stroke survivors. Finally, the role of the first author as the participant's primary contact during muscle activity tracking and his interviewer may have led to acquiescence bias or researcher bias during the qualitative interview. However, this in-depth engagement also allowed the establishment of a rapport and trust between the researcher and participant over time, serving as a potential mitigating factor [45].