Abstract:
Healthcare equipment include a vast range of goods, from basic equipment to complex software
systems. Incorporating software into such equipment is difficult since it requires market permission
and approval from regional regulatory organizations. As a consequence, medical enterprises must
oversee both the creation of these equipment and compliance with regulatory norms and standards.
While regulatory organizations do not specify a particular model, they do need careful consideration.
Plan-driven techniques, on the other hand, tend to stifle software development and shifts, while agile
techniques are frequently criticized for insufficient preparation and paperwork.
The goal of our investigations is to offer an adequate process framework for developing health care
devices while taking regulatory constraints into account. We first introduced the Improved Agile the
V-Model (EAV) after conducting a thorough examination of the previous research and McHugh's
suggested framework. This model combines plan-driven and agile methodologies. We then linked
the suggested solution with the MDEVSPICE architecture to verify that it meets the IEC62304
standard. Finally, we assessed the suggested model using an actual case study utilizing a wave therapy
device for medicine.
The EAV strategy flexibility for both waterfall and agile processes makes it easier to incorporate
novel demands into medical equipment, and the suggested systems design methodology helps in
software and hardware interaction. Connecting the EAV paradigm to the MDEVSPICE infrastructure
indicates total compliance with requirements. In addition, the proposed approach was statistically
tested and effectively executed in our particular study. We assessed equipment usage along with
effectiveness indicators, and most questions had a trust level of P<0.05.
The suggested design meets regulatory requirements and has already been used effectively in the
production of a wave therapy equipment. However, its usefulness for smaller and simple medical
goods need to be confirmed, which can be evaluated via the model.
