Founded in China seven years ago, Hanflag produces a selection of drumming accessories and practice tools that include sticks, stick bags and even cajons.
Its range of drum practice pads boast a wealth of colour and size options, from 6" to 12" pads, 4" knee pads and ‘sticky’ pads designed to grip to any surface. Today we’re taking a look at the Metronome Practice Pad complete with in-built metronome.
The 12" octagonal pad has a familiar aesthetic, with a chunky wooden base that’s finished in a dark natural wood colour, plus a rubber playing surface, which rebounds well and feels much like any other generic practice pad. A section of the rubber has been cut out to make way for the integrated metronome component.
Utilising a rechargeable battery (minimum battery life eight hours), the metronome also features a micro-USB port for charging, a mini-jack headphone out and a master volume control. On the front of the unit there is a small LCD screen, rotary encoder and an in-built speaker that is plenty loud enough to be heard over the clattering of sticks.
The metronome is capable of playing three different sounds, changing time signature from 1-9 and it also has a selection of eight subdivisions and syncopated rhythms to choose from. The LED lights above the screen are useful for indicating which beat of the bar you are on, changing from red to green and even moving left to right with each pulse.
The trigger sensor under the pad allows for tap tempo and there’s also a ‘train’ function that counts the number of strokes played within a set time limit (not the most useful function but it’s undoubtedly good fun for younger or competitive drummers).
There are two independent volume controls, which should allow for differentiation between accented and non-accented notes, but the system isn’t perfect. Rather than just making the chosen subdivision quieter it also makes some of the stronger beats quieter - which is far from ideal.
Despite its basic nature, the metronome pad certainly does the job, and, let's face it, the convenience of having everything combined in one is surprisingly novel and a welcome feature. Ideally, we’d like to see more advanced training features in subsequent models.